We would like to thank Dr. Tamara Bushnik and the NYULMC Rusk Research Team for their thoughts, suggestions, and contributions. This research was supported by 5K12 HD001097 (to J-RR, MSL, and PR).

1. Participant
<ol>
	<li>Recruit control participants older than 18 years, without a history of neurological dysfunction, significant eye injury, significant depression, major disability and/or electrical implants.</li>
	<li>Recruit Stroke participants older than 18 years, with a history of brain injury in the middle cerebral artery (MCA) distribution, have the ability to complete the Fugl-Meyer Scale, maintain a full range of eye movements35,36, have the ability to perform pointing tasks, and without the history of additional neurological dysfunction, significant eye health comorbidity, significant depression, major disability and/or electrical implants.</li>
	<li>Ask participants to sign a consent form approved by the Institutional Review Board of New York University&#8217;s School of Medicine.</li>
	<li>Participant Screening (for detailed exclusion criteria please see Rizzo et al37)
	<ol>
		<li>Take history and perform clinical examinations as discussed below.
		<ol>
			<li>Assess the cognitive state of participants with Mini Mental State Examination (MMSE)38.</li>
			<li>Perform neurological examination.</li>
			<li>Examine extraocular muscles and eye movements.
			<ol>
				<li>Ask the participants to follow the researcher&#8217;s finger with their eyes while keeping their head in one position. Draw an imaginary H letter in front of them and make sure that your finger moves far enough out and up/down, assessing center, up, down, left, right, down/left, down/right, up/left, and up/right.</li>
				<li>Ask the participants to follow and maintain the gaze on an object moved slowly through their visual field to assess smooth pursuit. Cover a distance of approximately 24 inches and using a pencil as a target, sweep back and forth slowly in horizontal and vertical directions, repeating each three times.</li>
				<li>Ask participants to look as fast as possible between 2 targets that are placed 24 inches apart to assess saccades. Use a pencil and a pen as targets and direct gaze to the targets in a back and forth manner three times horizontally and vertically.</li>
				<li>Ask the participants to fixate on an object as it moves slowly towards to their eyes to assess convergence, centering the target, a pencil, on the bridge of their nose. Following this procedure, repeat the test by bringing the same target from the nose back out to the starting position (divergence).</li>
				<li>Ask the patient to cover one eye and look at the researcher&#8217;s nose. Move the hand out of the patient&#8217;s visual field and then bring it in, wag the finger slowly and ask the patient to let the researcher know when the hand comes back into view, repeat this for upper left, upper right, lower left, and lower right quadrants. 
				NOTE: When the patient covers their right eye, cover the left eye, and vice versa.</li>
			</ol>
			</li>
			<li>Assess the visual impairment by a visual-motor Integration test.</li>
			<li>Assess the visual acuity by Snellen chart39,40.</li>
			<li>Assess the visual field with confrontation and if in question, perform Goldman or Humphrey visual field testing41,42.</li>
			<li>Assess hemi-spatial neglect via line bisection test and the single letter cancellation test43.</li>
			<li>Quantify the extent of disability via 25-item National Eye Institute Visual Functioning Questionnaire (NEI-VFQ-25) and a 10-item supplement survey44.</li>
		</ol>
		</li>
	</ol>
	</li>
</ol>
2. Preparation for the experiment and the physical configuration of equipment
<ol>
	<li>Equipment:
	<ol>
		<li>Choose an eye tracker
		<ol>
			<li>Choose an eye tracker that is capable of head-mounted use (to avoid interference with desk-based reach movements) high spatial resolution (&#8804;0.1o) and high temporal resolution (&#8805;250 Hz).</li>
			<li>Record the binocular eye movement with the eye tracker at a sampling rate of 250 Hz (sampling eye position every 4 ms) tracking both pupil and corneal reflection.</li>
		</ol>
		</li>
		<li>Choose of a limb tracker
		<ol>
			<li>Choose a limb tracker that can map the movement in the x, y, z position, &#179; 0.08 cm accuracy, Latency &#179; of 3.5 ms.</li>
		</ol>
		</li>
		<li>Choose a laptop capable of running a customized script that controls real-time integration of data acquired from two systems and co-registering the signals in real-time (Table of Materials).</li>
		<li>Choose a display monitor capable of integrating with the chosen laptop and that is large enough to support one-to-one correspondence between monitor and tabletop reach space</li>
		<li>Define a rectangle identical in size to the display monitor on a table surface between the participant and the display monitor, to use as a functional reaching space for experimental work.</li>
	</ol>
	</li>
	<li>Set up preparation:
	<ol>
		<li>Set up a table with the height adjustable chair.</li>
		<li>Place a display monitor 40 cm from the far edge of the table (Table of Materials).</li>
		<li>Place a tabletop board (reaching surface) with the 1-1 ratio dimension with the display monitor.</li>
		<li>Set up the limb tracker by mounting the electromagnetic source under the table (Table of Materials).</li>
		<li>Set up the eye tracker, host PC (Table of Materials).
		<ol>
			<li>Attach four infrared (IR) illuminators to four corners of the monitor using straps.</li>
			<li>Set the eye tracker configurations from eye tracker setup options screen.
			<ol>
				<li>Select 13-point calibration from the pre-set configuration of the eye tracker.</li>
				<li>Select the high saccade sensitivity to detect small saccade.</li>
				<li>Select Pupil-CR mode to record both pupils and cornea.</li>
				<li>Select a sampling rate at 250 Hz.</li>
			</ol>
			</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Participant physical preparation
	<ol>
		<li>Seat participants on a height-adjustable chair at the table with the computer display.</li>
		<li>Position the participant 60 cm away from the display monitor (Table of Materials).</li>
		<li>Fix the motion sensor (Table of Material) to the distal aspect of the index finger of the hand of the to be tested arm (dominant arms for controls, and both arms in participants with stroke)</li>
		<li>Place the eye tracker on the participants&#8217; headband and adjust the headband and cameras (Table of Materials).
		<ol>
			<li>Fitting the headband
			<ol>
				<li>Adjust the tightness and position of the headband (using headband knobs) so that the front pad is in the center of the forehead and the side pads above the participant&#8217;s ears.</li>
				<li>Make sure that the headband camera is in the center of the forehead and over the bridge of the nose.</li>
				<li>Ask participants to raise their eyebrows, and if the headband moves, refit it higher or lower on the forehead.</li>
			</ol>
			</li>
			<li>Adjust the camera and corneal illuminator position. Ask the participants to look at the display monitor.
			<ol>
				<li>From the camera screen, select the head camera image, verify that it shows four large spots from the IR markers that are positioned in the center of the head camera image. If they are not in the center, adjust accordingly.</li>
				<li>From the camera setup screen, select one eye at the time. Adjust the two eye cameras by lowering and raising the eye camera handle till the pupil of the eye is in the center of the camera image</li>
				<li>Focus the eye camera by rotating the lens holder.</li>
				<li>Set the pupil threshold by pressing the Auto Threshold button on the camera setup screen.</li>
				<li>Perform the same adjustment for the other eye.</li>
			</ol>
			</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Calibration
	<ol>
		<li>Calibrate the limb tracker output to reaching surface using a 9-point calibration, ask the participant to place their sensor attached finger on reaching surface (tabletop) locations as displayed on the monitor screen.</li>
		<li>Calibrate the eye tracker, ask participants to look at the calibration target that appears as a blue dot and maintain fixation until the next dot appears on the screen 
		NOTE: Calibration targets appear in 13 randomly selected positions on the screen</li>
		<li>Calibrate the eye tracker at least twice per session, first one at the start of the experiment and at its halfway point.</li>
	</ol>
	</li>
</ol>
3. Experiment
<ol>
	<li>Ask participants to move their finger onto the start position, covering the start circle on the screen with the finger-indicator dot (red dot), while fixating (eye) the start position on the screen. 
	NOTE: The start position is a correspondent location of the fixation point (blue dot) displays on the center of the screen (Figure 1a). The position of the finger is represented as 4 mm radius red dot on the screen.</li>
	<li>Require participants to maintain finger position on the start circle for 150 ms until the target appears.</li>
	<li>Ensure that participants fixate the start position until they hear a beep sound (&#8220;go beep&#8221;). (Figure 1) 
	NOTE: The duration between target appearance and the go signal is randomized between 250 to 750 ms to prevent anticipation of the go signal.</li>
	<li>Instruct participants to move both their eyes and fingertip quickly and accurately to the designated target as they hear the beep sound (Figure 1)
	<ol>
		<li>Designated target appears 1 cm radius white circle</li>
	</ol>
	</li>
	<li>Instruct participants to touch the tabletop location at the position of the virtual target as displayed on the screen by lifting the hand and finger and re-connecting the fingertip and tabletop
	<ol>
		<li>Make sure participants make a pointing movement by lifting the hand and finger rather than dragging the hand and finger on the tabletop.</li>
		<li>Display the end location of the reach as a red dot, following reach completion.</li>
		<li>Determine reach completion by a combination of low-velocity (&#60;5% peak) and 3 mm z-plane threshold.</li>
	</ol>
	</li>
	<li>Ask participants to perform a series of familiarization trials before starting data acquisition.</li>
	<li>Start data acquisition after participants touched 5 of the last 10 targets successfully.</li>
	<li>Ask participants to perform a series of look and reach trials as they were instructed during familiarization trials.
	<ol>
		<li>Have participants perform a total of 76 trials.</li>
	</ol>
	</li>
	<li>Have control participants perform the experiment with their dominant hand.</li>
	<li>Whenever it is possible, have participants with stroke perform the experiment with both the hands, more-affected and less-affected.</li>
	<li>Participants complete the entire experiment with at least one hand.</li>
</ol>
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/58885/58885fig1.jpg" /> 
Figure 1. Schematic view of setup and experiment. (a) Schematic representation of display monitor and reaching surface during a trial. (b) Sequencing of actions within visually-guided reach. First Fixation (F) appears. The target (T) appears after a randomized length of time. The &#8216;go&#8217; signal occurs as auditory beep sound (signified by the light-grey vertical bar) after an unpredictable time interval (concurrent offset of F) following by target appearance. Hand (H) and Eye (E) movements follow the go-signal. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58885/58885fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The advent of eye and hand tracking systems as available tools for objectively exploring the characteristics of ocular-manual motor systems has accelerated research studies, enabling a nuanced recording approach for an essential task in daily activities &#8211; eye-hand coordination. Many natural action-dependent tasks are visually guided and depend on vision as a primary sensory input. Gaze is programmed through ocular motor commands which point central vision at key spatial targets; this information is pivotal and assists in acquiring hand goals. The key is that coordinated eye-hand behavior must be executed efficiently and accurately. For example, deciding to grab a coffee cup will result in a rapid eye movement to the handle, a terminal fixation, the acquisition of pivotal environmental detail for index finger placement and prehension, all in temporally synchronized series. Following movement initiation, visual feedback of the upper limb is crucial for online error monitoring and correction.
Assessment of eye-hand coordination with our distinct methodology indicates that stroke hampers the coordination of eye-hand movement control. Stroke participants with MCA-injury reveal both less accurate saccades and reach (in both less/more-affected sides) relative to healthy controls; there also appears to be stark decoupling between the primary saccade onset and reach onset in both less-/more-affected sides. While impairments of eye and hand movement contribute separately to functional compromise, there appears to be a specific deficit in eye-hand coordination, which may amplify reaching errors and further compromise neurologic function; this occurs when these separate effector systems fail to coordinate toward a single synchronous behavior. One potential explanation may lie in the additional computational load of executing dual eye-hand movements and the related interference effects46,47,48,49. Experimental paradigms that require eye-hand movement co-registration permit scientists to systematically probe dual tasks; this is especially relevant to pathologic populations that have known difficulties with such tasks, regardless of the combination (cognitive-motor, motor-motor, etc)50,51,52.
Eye and upper limb movements are sensitive markers of cerebral injury and myriad applications exist diagnostically, prognostically, and therapeutically53,54,55,56,57,58,59. Eye movements and their relationships to limb movements create an even greater &#8216;window&#8217; into the brain than previously thought. Aside from direct impairment in eye movement function, deficits in eye movement compensation in response to hand movement impairment is a new area rife with scientific opportunity. Once further characterized, eye-hand coordination will be capable of shedding light on multiple applications and motivate further studies to understand its full implications for functional movement control, translating mechanistic insight into clinical knowledge. The key to eye-hand control research is the robust methodology and vigorous protocols that enable one to assay such physiology concurrently and with high fidelity.
Despite the benefits delineated here, there are still methodological limitations present. As described in the methods section, participants are instructed to fixate the target as it appears on a display monitor and to make a concurrent reach on a tabletop positioned immediately in front of the workstation. This requires a transformation of spatial information from the monitor to the tabletop and adds an extra cognitive step. While this cognitive challenge is identical to the transformation one makes during computer work, translating information from the screen to the work station or into mouse-keyboard &#8216;space&#8217;, a more naturalistic task would use a translation-free paradigm. Regardless, robust 3-D hand tracking with objectively characterized eye recordings allow one to probe integrated motor control that revolves around multi-effector coordination. In addition, the present approach affords an opportunity to assess the eye-hand control aspects critical to interaction with the computer interface in real-time.
While quantitative dual-effector recordings in 3-D afford robust opportunities within ocular-manual motor investigations in the setting of ABI, the feasibility of such dual recordings for both eye and hand is challenging, particularly in a pathological setting when executed with research-grade rigor. Efforts have attempted to combine eye and hand tracker to assess eye and hand physiology, but the data output is often unstable 60. When these instabilities seen in healthy populations are taken into account and juxtaposed with the technical calibration and recording issues in participants with pathology, the data becomes less and less useful. Hence, it is pragmatic to leverage a method and paradigm, as described here. Accordingly, eye position calibration is completed in the depth plane of interest, eye-specific stimuli are displayed at this single distance and gaze measurement fidelity is subsequently robust. At other distances, the eye&#8217;s view is no longer aligned, and characterization is limited to 3-D recordings of hand position61,62. The quintessential study of the eye and hand in the pathologic setting will be best achieved with custom software that permits multi-depth calibrations, integrated hardware, a central computer or host system for signal co-registration, and a protocol similar to the one aforementioned.

A critical element of the neurological function is eye-hand coordination or the integration of ocular and manual motor systems for the planning and execution of combined function towards a shared goal, for example, a look, reach and grab of the television remote. Many purposeful tasks depend on visually guided actions, such as reaching, grasping, object manipulation and tool use, which hinge on the temporally and spatially coupled eye and hand movements. Acquired brain injuries (ABI) cause not only limb dysfunction but also ocular dysfunction; more recently, there is also evidence pointing to the dysfunction of eye-hand coordination1. Coordinated eye-hand motor control programs are susceptible to insult in neurological injuries from vascular, traumatic and degenerative etiologies. These insults may cause a breakdown between any of the indispensable relationships needed for the integrated and rapid motor control2,3,4,5,6. Many studies on the manual motor function have been completed and have leveraged visual guidance as a core pillar of the paradigm without a method or protocol in place to analyze eye movements concurrently.
In ABI, conspicuous motor deficits are often detected during the bedside clinical examination. However, concurrent ocular motor impairments and complex impairments involving the integration of sensory and motor systems may be subclinical and necessitate objective recording to be identified7,8,9,10,11,12,13,14,15,16. Ocular-manual motor coordination depends on a large and interconnected cerebral network, highlighting the need for a detailed study. An eye-hand coordination evaluation with dual objective recordings provides an opportunity to assay both cognitive and motor function in multiple populations, including healthy controls and subjects with a history of brain injury, thus providing insight into cerebral circuitry and function3.
While saccades are ballistic movements that can vary in amplitude depending on task need, studies have shown dependencies between saccade and hand movement during visually guided action17,18,19,20. In fact, recent experiments have demonstrated that control systems for both movements share planning resources21,22. The motor planning hub for eye-hand coordination lies in the posterior parietal cortex. In a stroke, there are well-known deficits in motor control; hemiparetic patients have been shown to generate inaccurate predictions given a set of neural commands, when asked to perform visually guided hand movements, using either the more affected (contralateral) or less affected (ipsilateral) limb23,24,25,26,27,28,29. Furthermore, eye-hand coordination and related motor control programs are susceptible to insult following neurological injuries, decoupling the relationships, temporally and spatially, between effectors30. Objective recordings of eye and hand control are paramount to characterizing the incoordination or degree of coordination impairment and improves the scientific understanding of eye-hand motor control mechanism in a functional context.
Although there are many studies of eye-hand coordination in healthy controls17,31,32,33,34, our group has advanced the field by our setting of neurological injury, for instance during stroke circuitry assessment, have investigated the spatial and temporal organization of hand movements, often in response to visually displayed spatial targets. Studies that have expanded the objective characterization to eye and hand have almost exclusively focused on the performance capacity to record both effectors post-stroke or in pathologic settings; the described protocol enables robust characterization of ocular and manual motor control in unconstrained and natural movements. Here we describe the technique in an investigation of visually-guided saccade-to-reach movements in subjects with chronic middle cerebral artery (MCA) stroke relative to healthy controls. For the simultaneous recording of saccade and reach, we employ concurrent eye and hand motion tracking.

<table border="0" cellpadding="0" cellspacing="0" style="width:647px;" width="646">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:215px;">27.0&#34; Dell LED-Lit monitor&#160;</td>
			<td style="width:152px;">Dell</td>
			<td style="width:101px;">S2716DG</td>
			<td style="width:179px;">QHD resolution (2560 x 1440)</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:215px;">ASUS ROG G750JM 17-Inch&#160;</td>
			<td style="width:152px;">AsusTek Computer Inc</td>
			<td style="width:101px;"></td>
			<td></td>
		</tr>
		<tr height="105">
			<td height="105" style="height:105px;width:215px;">Eye Link II</td>
			<td style="width:152px;">SR-Research</td>
			<td style="width:101px;">500 Hz binocular eye monitoring 
			0.01 &#186; RMS resolutions</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:215px;">Matlab</td>
			<td style="width:152px;">MathWorks</td>
			<td style="width:101px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:215px;">Polhemus MicroSensor 1.8&#160;</td>
			<td style="width:152px;">Polhemus</td>
			<td style="width:101px;"></td>
			<td>240&#160;Hz, 0.08&#160;cm accuracy</td>
		</tr>
	</tbody>
</table>

efficiently recording the eye-hand coordination to incoordination spectrum

The objective analysis of eye movements has a significant history and has been long proven to be an important research tool in the setting of brain injury. Quantitative recordings have a strong capacity to screen diagnostically. Concurrent examinations of the eye and upper limb movements directed toward shared functional goals (e.g., eye-hand coordination) serve as an additional robust biomarker-laden path to capture and interrogate neural injury, including acquired brain injury (ABI). While quantitative dual-effector recordings in 3-D afford ample opportunities within ocular-manual motor investigations in the setting of ABI, the feasibility of such dual recordings for both eye and hand is challenging in pathological settings, particularly when approached with research-grade rigor. Here we describe the integration of an eye tracking system with a motion tracking system intended primarily for limb control research to study a natural behavior. The protocol enables the investigation of unrestricted, three-dimensional (3D) eye-hand coordination tasks. More specifically, we review a method to assess eye-hand coordination in visually guided saccade-to-reach tasks in subjects with chronic middle cerebral artery (MCA) stroke and compare them to healthy controls. Special attention is paid to the specific eye- and limb-tracking system properties in order to obtain high fidelity data from participants post-injury. Sampling rate, accuracy, permissible head movement range given anticipated tolerance and the feasibility of use were several of the critical properties considered when selecting an eye tracker and an approach. The limb tracker was selected based on a similar rubric but included the need for 3-D recording, dynamic interaction and a miniaturized physical footprint. The quantitative data provided by this method and the overall approach when executed correctly has tremendous potential to further refine our mechanistic understanding of eye-hand control and help inform feasible diagnostic and pragmatic interventions within the neurological and rehabilitative practice.&#160;

Thirty participants participated in the research study. There were 17 participants in the control cohort, and 13 participants in the stroke cohort. Two participants couldn&#8217;t finish the whole experiment, so their data were excluded from the analysis.
Demographics and Questionnaire Assessments
Table 1 shows the clinical and demographic characteristics of the representative stroke cohort.
Mean unweighted VFQ scores were 91.33 &#177; 13.01 in stroke participants, versus 94.87 &#177; 4.87 in healthy controls (p=0.203, ns). Mean scores of the 10-item supplement were 95 &#177; 11.57 in stroke participants, versus 96.27 &#177; 6.64 in healthy controls (p=0.375, ns). Mean scores for the composite and 10-item supplement were 92.36 &#177; 12.18 in stroke participants, versus 95.12 &#177; 4.65 in healthy controls (p=0.244, ns). Stroke participants had a mean Fugl-Meyer score of 55.54 &#177; 13.33, with a range of 30-66.
Eye and Hand Movements Durations and Latencies 
In Figure 2 saccade and reach latencies, measured as the duration between the go signal and movement onset, are plotted. Stroke participants made the initial (primary) saccades significantly earlier in both less-affected and more-affected sides, comparing to healthy control participants (p&#60;.05) (more-affected hand: 0.082 s, CI: [0.052 0.112]; less-affected hand: 0.106 s, CI: [0.08 0.132]; control saccade onsets: 0.529 s, CI: [0.514 0.543]). Compare to control, stroke participants made remarkably early initial saccade to target but there were no significant differences between control reach onsets and less-affected or more-affected reach onsets in stroke participants (less-affected hand: 0.545 s, CI: [0.521 0.568]; more-affected hand: 0.60 s, CI: [0.567 0.632]; control reach onsets: 0.556 s, CI: [0.544 0.568]). Latency between the initial saccade and reach onset, which represents a temporal decoupling in stroke participants, was greater in in both the more-affected and less-affected hand, a 519 ms (CI: [476 562]) and a 439 ms (CI: [404 474]) separation respectively in stroke, versus a minimal separation of 27 ms (CI: [8.5 45]) in controls (all p&#60;.05). Stroke participants not only made the longest duration reaches (computed as the difference between movement onset and termination) with their more-affected side (604 ms, CI: [587 622]) but also increased their average reach time on the less-affected side (546 ms, CI: [537 555] vs 352 ms, CI: [348 356]) (all p&#60;.05).
Eye Movements Frequency
We examined the interval between the initial saccade onset and reach onset, which was minimal in healthy controls and significantly longer in stroke participants in the less- and more- affected side. We noticed differences in the number of saccades that were made during this period. The number of saccades produced by stroke participants regardless of the limb they used, was more than healthy controls. We plotted the number of secondary saccades made by participants in histograms (Figure 3). Healthy controls in 90% of trials made a single saccade and sustained fixation at the target until they completed the reach. In sharp contrast, this pattern was generated in 50% of trials (z = 32.2, p&#60;.05) for those with stroke and the remainder made multiple saccades. (Figure 3). Figure 4 shows an example of such saccade traces.
Spatial Errors of the Eye and Hand Movements
With regard to the amplitude from movement endpoint to target center (movement error), stroke participants had increased reach errors in both less and more affected hands relative to healthy controls (control: 9.3 mm, CI: [9.0 9.5]; less-affected arm: 19.2 mm, CI: [18.4 20.0]; more-affected arm: 21.4 mm, CI: [20.5 21.4]) (Figure 5; all p&#60;.05). Along with the increase in reach errors, saccade endpoint errors increased greatly as shown in Figure 5 (control: 18.3 mm, CI: [17.9 18.7]; less-affected arm: 36.4 mm, CI: [35.2 37.6]; more-affected arm: 41.6 mm, CI: [40.3 43.0]; all p&#60;.05).
Arm Motor Impairment and Eye-Hand Latency Decoupling Correlation
The Fugl-Meyer score was used to assess arm motor impairment. It was expected that temporal decoupling in stroke participants would correlate with arm motor impairment severity, but our results demonstrated that it was statistically insignificant for the less (r = -0.64, ns) and more affected (r = -0.34, ns) arms.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>ID</td>
			<td>Age</td>
			<td>Sex</td>
			<td>H / H a</td>
			<td>Stroke&#160;</td>
			<td>Chronicity (yrs)</td>
			<td>Fugl-Meyer Score c</td>
		</tr>
		<tr>
			<td></td>
			<td>(yrs)</td>
			<td></td>
			<td></td>
			<td>Characteristics b</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>1</td>
			<td>78</td>
			<td>M</td>
			<td>R/L</td>
			<td>R MCA distribution</td>
			<td>2</td>
			<td>66</td>
		</tr>
		<tr>
			<td>2</td>
			<td>61</td>
			<td>F</td>
			<td>R/L</td>
			<td>R MCA distribution</td>
			<td>7</td>
			<td>66</td>
		</tr>
		<tr>
			<td>3</td>
			<td>34</td>
			<td>M</td>
			<td>R/R</td>
			<td>L MCA distribution</td>
			<td>1.7</td>
			<td>66</td>
		</tr>
		<tr>
			<td>4</td>
			<td>39</td>
			<td>F</td>
			<td>R/R</td>
			<td>L MCA distribution</td>
			<td>1.4</td>
			<td>45</td>
		</tr>
		<tr>
			<td>5</td>
			<td>70</td>
			<td>M</td>
			<td>R/R</td>
			<td>L MCA distribution</td>
			<td>2.8</td>
			<td>58</td>
		</tr>
		<tr>
			<td>6</td>
			<td>60</td>
			<td>F</td>
			<td>R/L</td>
			<td>R MCA distribution</td>
			<td>2.6</td>
			<td>30</td>
		</tr>
		<tr>
			<td>7</td>
			<td>73</td>
			<td>M</td>
			<td>R/L</td>
			<td>R MCA distribution</td>
			<td>6</td>
			<td>58</td>
		</tr>
		<tr>
			<td>8</td>
			<td>51</td>
			<td>F</td>
			<td>R/L</td>
			<td>R MCA distribution</td>
			<td>12.2</td>
			<td>30</td>
		</tr>
		<tr>
			<td>9</td>
			<td>60</td>
			<td>M</td>
			<td>R/R</td>
			<td>L MCA distribution</td>
			<td>4.4</td>
			<td>63</td>
		</tr>
		<tr>
			<td>10</td>
			<td>39</td>
			<td>M</td>
			<td>R/L</td>
			<td>R MCA distribution</td>
			<td>4.7</td>
			<td>47</td>
		</tr>
		<tr>
			<td>11</td>
			<td>70</td>
			<td>M</td>
			<td>R/L</td>
			<td>R MCA distribution</td>
			<td>2</td>
			<td>66</td>
		</tr>
		<tr>
			<td>12</td>
			<td>47</td>
			<td>F</td>
			<td>R/R</td>
			<td>L MCA distribution</td>
			<td>1.5</td>
			<td>61</td>
		</tr>
		<tr>
			<td>13</td>
			<td>65</td>
			<td>F</td>
			<td>R/R</td>
			<td>L MCA distribution</td>
			<td>0.7</td>
			<td>66</td>
		</tr>
		<tr>
			<td>Avg</td>
			<td>57.5</td>
			<td></td>
			<td></td>
			<td></td>
			<td>3.8</td>
			<td>55.5</td>
		</tr>
		<tr>
			<td>(SD)</td>
			<td>-14.3</td>
			<td></td>
			<td></td>
			<td></td>
			<td>-3.2</td>
			<td>-13.3</td>
		</tr>
	</tbody>
</table>
TABLE 1. Stroke Clinical Characteristics. 
a &#8220;H/H&#8221; = Handedness / Hemiparesis: Handedness (assessed through Edinburgh Inventory) / Hemiparesis Laterality
b &#8220;Stroke Features&#8221;: lesion location obtained from medical history with participant and/or family members serving as historian; region and laterality cross-validated for consistency with examination findings 
c &#8220;Fugl-Meyer Score&#8221;: a summation of the Upper Extremity Score [total possible 66], which reflects the extent of post-stroke motor impairment.
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/58885/58885fig2.jpg" /> 
Figure 2. Saccade and Reach Latencies Saccade onsets (indicated by blue circles) occur significantly earlier in the stroke participants, while there were no significant differences between control reach onsets (indicated by green circles) and stroke participants (indicated by green circles) (with a slight delay on the more-affected side). Latency between the initial saccade and reach onset is indicated with a light grey bar. (onsets: circles, terminations: squares) (error bar: 95% Confidence Interval) <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58885/58885fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/58885/58885fig3.jpg" /> 
Figure 3. Histograms of the number of saccades in addition to the primary saccade. The upper histogram shows, control participants overwhelmingly make a primary saccade only. There were either no additional saccades beyond the primary saccade or contain a single secondary saccade in about 96% trials. The lower histogram shows stroke participants, make up to five secondary saccades in the same 96% of trials. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58885/58885fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/58885/58885fig4.jpg" /> 
Figure 4. Figure shows, random raw saccade trace from two control participants and two stroke participants. Two samples (unfiltered, raw) eye (blue) and hand (green) traces from control participants (left column), and stroke participants (right column) are plotted in screen mm to allow for simultaneous plotting of eye and hand traces. In two stroke participants trials, multiple eye movements are made before they complete the reach, as opposed to control participants trials that make a single saccade at or close the time of the reach. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58885/58885fig4large.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/58885/58885fig5.jpg" /> 
Figure 5. Average endpoint error by participant grouping and/or arm Green bars indicate average reach error, and blue bars indicate average saccade (primary)&#160; error. Two-sample t-tests were performed. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58885/58885fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Efficiently Recording the Eye-Hand Coordination to Incoordination Spectrum at JoVE.com

Efficiently Recording the Eye-Hand Coordination to Incoordination Spectrum

Cerebral injury can damage both ocular and somatic motor systems. Characterization of motor control post-injury affords biomarkers that assist in disease detection, monitoring, and prognosis. We review a method to measure eye-hand movement control in health and in pathologic incoordination, with look-and-reach paradigms to assess coordination between eye and hand.

The objective analysis of eye movements has a significant history and has been long proven to be an important research tool in the setting of brain ...

efficiently-recording-eye-hand-coordination-to-incoordination

Nanyang Technological University

Research

JoVE Journal

Behavior

7.8K Views.  New York University Langone Health. Cerebral injury can damage both ocular and somatic motor systems. Characterization of motor control post-injury affords biomarkers that assist in disease detection, monitoring, and prognosis. We review a method to measure eye-hand movement control in health and in pathologic incoordination, with look-and-reach paradigms to assess coordination between eye and hand.

Video: Efficiently Recording the Eye-Hand Coordination to Incoordination Spectrum

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

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

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

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

Applying Stereotactic Injection Technique to Study Genetic Effects on Animal Behaviors

Stereotactic injection is a useful technique to deliver high titer lentiviruses to targeted brain areas in mice. Lentiviruses can either overexpress or knockdown gene expression in a relatively focused region without significant damage to the brain tissue. After recovery, the injected mouse can be tested on various behavioral tasks such as the Open Field Test (OFT) and the Forced Swim Test (FST). The OFT is designed to assess locomotion and the anxious phenotype in mice by measuring the amount of time that a mouse spends in the center of a novel open field. A more anxious mouse will spend significantly less time in the center of the novel field compared to controls. The FST assesses the anti-depressive phenotype by quantifying the amount of time that mice spend immobile when placed into a bucket of water. A mouse with an anti-depressive phenotype will spend significantly less time immobile compared to control animals. The goal of this protocol is to use the stereotactic injection of a lentivirus in conjunction with behavioral tests to assess how genetic factors modulate animal behaviors.

Stereotactic injection of lentiviruses expressing cDNAs or shRNAs can modulate gene expression in specific brain areas of mice. Here, we present a protocol to combine stereotactic injections with behavioral tasks, such as the Open Field Test (OFT) and the Forced Swim Test (FST).

Stereotactic injection is a useful technique to deliver high titer lentiviruses to targeted brain areas in mice. Lentiviruses can either overexpress or ...

Testing Sensory and Multisensory Function in Children with Autism Spectrum Disorder

In addition to impairments in social communication and the presence of restricted interests and repetitive behaviors, deficits in sensory processing are now recognized as a core symptom in autism spectrum disorder (ASD). Our ability to perceive and interact with the external world is rooted in sensory processing. For example, listening to a conversation entails processing the auditory cues coming from the speaker (speech content, prosody, syntax) as well as the associated visual information (facial expressions, gestures). Collectively, the &#8220;integration&#8221; of these multisensory (i.e., combined audiovisual) pieces of information results in better comprehension. Such multisensory integration has been shown to be strongly dependent upon the temporal relationship of the paired stimuli. Thus, stimuli that occur in close temporal proximity are highly likely to result in behavioral and perceptual benefits &#8211; gains believed to be reflective of the perceptual system&#39;s judgment of the likelihood that these two stimuli came from the same source. Changes in this temporal integration are expected to strongly alter perceptual processes, and are likely to diminish the ability to accurately perceive and interact with our world. Here, a battery of tasks designed to characterize various aspects of sensory and multisensory temporal processing in children with ASD is described. In addition to its utility in autism, this battery has great potential for characterizing changes in sensory function in other clinical populations, as well as being used to examine changes in these processes across the lifespan.

We describe how to implement a battery of behavioral tasks to examine the processing and integration of sensory stimuli in children with ASD. The goal is to characterize individual differences in temporal processing of simple auditory and visual stimuli and relate these to higher order perceptual skills like speech perception.

In addition to impairments in social communication and the presence of restricted interests and repetitive behaviors, deficits in sensory processing are ...

Combined Shuttle-Box Training with Electrophysiological Cortex Recording and Stimulation as a Tool to Study Perception and Learning

Shuttle-box avoidance learning is a well-established method in behavioral neuroscience and experimental setups were traditionally custom-made; the necessary equipment is now available by several commercial companies. This protocol provides a detailed description of a two-way shuttle-box avoidance learning paradigm in rodents (here Mongolian gerbils; Meriones unguiculatus) in combination with site-specific electrical intracortical microstimulation (ICMS) and simultaneous chronical electrophysiological in vivo recordings. The detailed protocol is applicable to study multiple aspects of learning behavior and perception in different rodent species.
Site-specific ICMS of auditory cortical circuits as conditioned stimuli here is used as a tool to test the perceptual relevance of specific afferent, efferent and intracortical connections. Distinct activation patterns can be evoked by using different stimulation electrode arrays for local, layer-dependent ICMS or distant ICMS sites. Utilizing behavioral signal detection analysis it can be determined which stimulation strategy is most effective for eliciting a behaviorally detectable and salient signal. Further, parallel multichannel-recordings using different electrode designs (surface electrodes, depth electrodes, etc.) allow for investigating neuronal observables over the time course of such learning processes. It will be discussed how changes of the behavioral design can increase the cognitive complexity (e.g. detection, discrimination, reversal learning).

Shuttle-box avoidance learning is well-established in behavioral neuroscience. This protocol describes how shuttle-box learning in rodents can be combined with site-specific electrical intracortical microstimulation (ICMS) and simultaneous chronical in vivo recordings as a tool to study multiple aspects of learning and perception.

Shuttle-box avoidance learning is a well-established method in behavioral neuroscience and experimental setups were traditionally custom-made; the ...

Concurrent Electroencephalography Recording During Transcranial Alternating Current Stimulation (tACS)

Oscillatory brain activities are considered to reflect the basis of rhythmic changes in transmission efficacy across brain networks and are assumed to integrate cognitive neural processes. Transcranial alternating current stimulation (tACS) holds the promise to elucidate the causal link between specific frequencies of oscillatory brain activity and cognitive processes. Simultaneous electroencephalography (EEG) recording during tACS would offer an opportunity to directly explore immediate neurophysiological effects of tACS. However, it is not trivial to measure EEG signals during tACS, as tACS creates a huge artifact in EEG data. Here we explain how to set up concurrent tACS-EEG experiments. Two necessary considerations for successful EEG recording while applying tACS are highlighted. First, bridging of the tACS and EEG electrodes via leaking EEG gel immediately saturates the EEG amplifier. To avoid bridging via gel, the viscosity of the EEG gel is the most important parameter. The EEG gel must be viscous to avoid bridging, but at the same time sufficiently fluid to create contact between the tACS electrode and the scalp. Second, due to the large amplitude of the tACS artifact, it is important to consider using an EEG system with a high resolution analog-to-digital (A/D) converter. In particular, the magnitude of the tACS artifact can exceed 100 mV at the vicinity of a stimulation electrode when 1 mA tACS is applied. The resolution of the A/D converter is of importance to measure good quality EEG data from the vicinity of the stimulation site. By following these guidelines for the procedures and technical considerations, successful concurrent EEG recording during tACS will be realized.

Concurrent Electroencephalography Recording During Transcranial Alternating Current Stimulation tACS

In this article we explain how to set up a concurrent transcranial alternating current stimulation and EEG experiment.

Oscillatory brain activities are considered to reflect the basis of rhythmic changes in transmission efficacy across brain networks and are assumed to ...

Recording Mouse Ultrasonic Vocalizations to Evaluate Social Communication

Mice emit ultrasonic vocalizations in different contexts throughout development and in adulthood. These vocal signals are now currently used as proxies for modeling the genetic bases of vocal communication deficits. Characterizing the vocal behavior of mouse models carrying mutations in genes associated with neuropsychiatric disorders such as autism spectrum disorders will help to understand the mechanisms leading to social communication deficits. We provide here protocols to reliably elicit ultrasonic vocalizations in pups and in adult mice. This standardization will help reduce inter-study variability due to the experimental settings. Pup isolation calls are recorded throughout development from individual pups isolated from dam and littermates. In adulthood, vocalizations are recorded during same-sex interactions (without a sexual component) by exposing socially motivated males or females to an unknown same-sex conspecific. We also provide a protocol to record vocalizations from adult males exposed to an estrus female. In this context, there is a sexual component in the interaction. These protocols are established to elicit a large amount of ultrasonic vocalizations in laboratory mice. However, we point out the important inter-individual variability in the vocal behavior of mice, which should be taken into account by recording a minimal number of individuals (at least 12 in each condition). These recordings of ultrasonic vocalizations are used to evaluate the call rate, the vocal repertoire and the acoustic structure of the calls. Data are combined with the analysis of synchronous video recordings to provide a more complete view on social communication in mice. These protocols are used to characterize the vocal communication deficits in mice lacking ProSAP1/Shank2, a gene associated with autism spectrum disorders. More ultrasonic vocalizations recordings can also be found on the mouseTube database, developed to favor the exchange of such data.

Mouse ultrasonic vocalizations are used as proxies to model the genetic bases of vocal communication deficits in mouse models for neuropsychiatric disorders. The present protocol describes three experimental contexts that reliably elicit ultrasonic vocalizations from pups (throughout development) and adult mice (same-sex interactions, male-estrus female interactions).

Mice emit ultrasonic vocalizations in different contexts throughout development and in adulthood. These vocal signals are now currently used as proxies ...

Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities

In both the East and West, traditional teachings say that the mind and heart are somehow closely correlated, especially during spiritual practice. One difficulty in proving this objectively is that the natures of brain and heart activities are quite different. In this paper, we propose a methodology that uses wavelet entropy to measure the chaotic levels of both electroencephalogram (EEG) and electrocardiogram (ECG) data and show how this may be used to explore the potential coordination between the mind and heart under different experimental conditions. Furthermore, Statistical Parametric Mapping (SPM) was used to identify the brain regions in which the EEG wavelet entropy was the most affected by the experimental conditions. As an illustration, the EEG and ECG were recorded under two different conditions (normal rest and mindful breathing) at the beginning of an 8-week standard Mindfulness-based Stress Reduction (MBSR) training course (pretest) and after the course (posttest). Using the proposed method, the results consistently showed that the wavelet entropy of the brain EEG decreased during the MBSR mindful breathing state as compared to that during the closed-eye resting state. Similarly, a lower wavelet entropy of heartrate was found during MBSR mindful breathing. However, no difference in wavelet entropy during MBSR mindful breathing was found between the pretest and posttest. No correlation was observed between the entropy of brain waves and the entropy of heartrate during normal rest in all participants, whereas a significant correlation was observed during MBSR mindful breathing. Additionally, the most well-correlated brain regions were located in the central areas of the brain. This study provides a methodology for the establishment of evidence that mindfulness practice (i.e., mindful breathing) may increase the coordination between mind and heart activities.

This manuscript describes how to use the wavelet entropy index to analyze high-density electroencephalography (EEG) and electrocardiography (ECG) data. We show that the irregularity of cerebral and cardiac activities became more coordinated during mindfulness-based stress reduction practice.

In both the East and West, traditional teachings say that the mind and heart are somehow closely correlated, especially during spiritual practice. One ...

Battery of Behavioral Tests Assessing General Locomotion, Muscular Strength, and Coordination in Mice

Behavioral testing is used in pre-clinical trials to assess the phenotypic effects and outcomes that a particular disease or treatment has on the animal&#39;s wellbeing and health. There are numerous behavioral tests that may be applied. We selected a test for general locomotion, the open field test (OFT); a test for muscular strength, the mesh test (MT); and a test for coordination, the rotarod test (RR). Testing can be accomplished on a weekly or monthly basis. As a test for general locomotion, the OFT works by objectively monitoring movement parameters while the mouse is in an open field apparatus. The field is generally a 2&#39; x 2&#39; box, and the movements are recorded through laser sensing or through video capture. The mouse is placed in the center of the open field and allowed to move freely for the test. The MT uses the latency for a mouse to fall off an inverted screen as a measure of muscular strength. A mouse is placed on a screen, which is inverted over a clear box, and is timed for their latency to fall. Three trials are performed, with the best of the three trials scored for that day. A score of 60 s is the maximum time a mouse is left inverted. Mice are given a 5-min rest period between mesh test trials. Lastly, an accelerated protocol on the RR assesses motor coordination and endurance. During a trial, a mouse walks on a rotating rod as it increases in speed from 4 rpm to 40 rpm over 5 min. The trial ends when the mouse touches the magnetized pressure sensor upon falling. Each mouse undergoes three trials, and the best trial is scored for that day. This combined behavioral data allows for the global assessment of mobility, coordination, strength, and movement of the test animals. At least two out of the three behavioral testing measures must show improvement for an animal to qualify as having overall improved motor function.

Behavioral testing is used in pre-clinical trials to assess the phenotypic effects of a disease or treatment on an animal's wellbeing. In order to globally assess motor functioning, we selected tests for general locomotion, muscular strength, and coordination: the open field test, the mesh test, and the rotarod test, respectively.

Behavioral testing is used in pre-clinical trials to assess the phenotypic effects and outcomes that a particular disease or treatment has on the ...

A Wireless, Bidirectional Interface for In Vivo Recording and Stimulation of Neural Activity in Freely Behaving Rats

In vivo electrophysiology is a powerful technique to investigate the relationship between brain activity and behavior at a millisecond and micrometer scale. However, current methods mostly rely on tethered cable recordings or only use unidirectional systems, allowing either recording or stimulation of neural activity, but not at the same time or same target. Here, a new wireless, bidirectional device for simultaneous multichannel recording and stimulation of neural activity in freely behaving rats is described. The system operates through a single portable head stage that both transmits recorded activity and can be targeted in real-time for brain stimulation using a telemetry-based multichannel software. The head stage is equipped with a preamplifier and a rechargeable battery, allowing stable long-term recordings or stimulation for up to 1 h. Importantly, the head stage is compact, weighs 12 g (including battery) and thus has minimal impact on the animal&#180;s behavioral repertoire, making the method applicable to a broad set of behavioral tasks. Moreover, the method has the major advantage that the effect of brain stimulation on neural activity and behavior can be measured simultaneously, providing a tool to assess the causal relationships between specific brain activation patterns and behavior. This feature makes the method particularly valuable for the field of deep brain stimulation, allowing precise assessment, monitoring, and adjustment of stimulation parameters during long-term behavioral experiments. The applicability of the system has been validated using the inferior colliculus as a model structure.

A Wireless, Bidirectional Interface for In Vivo Recording and Stimulation of Neural Activity in Freely Behaving Rats

A wireless, bidirectional system for multi-channel neural recordings and stimulation in freely behaving rats is introduced. The system is light and compact, thus having minimal impact on the animal&#180;s behavioral repertoire. Moreover, this bidirectional system provides a sophisticated tool to assess causal relationships between brain activation patterns and behavior.

In vivo electrophysiology is a powerful technique to investigate the relationship between brain activity and behavior at a millisecond and micrometer ...

A Semantic Priming Event-related Potential (ERP) Task to Study Lexico-semantic and Visuo-semantic Processing in Autism Spectrum Disorder

Individuals with autism spectrum disorder (ASD) have characteristic deficits in understanding the meaning of language, or semantic processing. However, some evidence indicates that semantic processing of non-linguistic stimuli is intact, suggesting that semantic deficits may be language-specific. To appropriately characterize semantic processing deficits in individuals with ASD, comparison of within-modality linguistic (e.g., written words) and non-linguistic (e.g., pictures) stimuli is required. This paper describes such a methodology that makes use of a semantic priming paradigm during concurrent recording of electroencephalographic (EEG) data. EEG provides a dynamic measure of brain activity that is well-suited to characterize subtle differences in semantic processing that may not be observable at the behavioral level. The semantic priming paradigm presents a prime picture or word (e.g., dog) followed by a target picture or word that is either related (e.g., cat) or unrelated (e.g., pencil) to the prime. This paradigm can thus be used to evaluate semantic processing across different modalities, and to compare lexico-semantic and visuo-semantic processing abilities in individuals with ASD and how they might differ from TD individuals. The specific steps involved in creating the stimuli, performing the EEG testing, and analyzing the EEG data are discussed. Representative results illustrate how the N400 component of the event-related potential (ERP) is reduced following semantically-related prime-target pairs compared to unrelated pairs. Comparisons of the N400 between conditions, modalities, and groups can provide estimates of the success of semantic processing, and can thereby be used to characterize semantic deficits in individuals with ASD or other clinical populations.

A Semantic Priming Event-related Potential ERP Task to Study Lexico-semantic and Visuo-semantic Processing in Autism Spectrum Disorder

This paper describes a semantic priming ERP task using within-modality pairs of pictures and words to investigate semantic processing in individuals with autism spectrum disorder (ASD).

Individuals with autism spectrum disorder (ASD) have characteristic deficits in understanding the meaning of language, or semantic processing. However, ...