This research was supported by NIH R21CA183492, the Simons Foundation, the Wallace Research Foundation, and by CTSA award UL1TR000445 from the National Center for Advancing Translational Sciences.

Ethics statement: All subjects must provide informed consent prior to the experiment. The research described here has been approved by the Vanderbilt University Medical Center&#8217;s Institutional Review Board.
1. Experiment Set Up
<ol>
	<li>Ask the participants to complete the tasks in a dimly lit, sound controlled room. 
	NOTE: Consider implementing a visual schedule29,30 as part of the study design. Although each task in this battery is relatively short, performing several tasks in a row can cause fatigue in some children, both with typical development (TD) and with ASD. A visual schedule should include all the planned activities (both tasks and hearing/vision screening), as well as short breaks between tasks. This structure will help contribute to an overall positive research experience for the participant, and has even been shown to elicit more accurate responses in some tasks31.</li>
	<li>Affix a chin rest to the table where the participant will sit while completing the task, with the computer monitor placed 60 cm away from the participant. This is to ensure that the stimuli are the same intensity for each participant. Use noise-cancelling headphones or speakers for auditory stimulus delivery.</li>
	<li>Due to differences in individual experimental platforms (sound card, graphics card, operating system, etc.), verify the stimulus duration and stimulus onset asynchronies (SOAs) with an oscilloscope, photovoltaic cell, and microphone on each computer for the experiment. 
	NOTE: Depending on the individual platform (for example, a slow sound card), make adjustments to the experiment code so that the timing of stimulus presentation is accurate.</li>
</ol>
2. Stimuli
<ol>
	<li>Generate 2 .wav or .mp4 files with duration of 16 msec (including a 2 - 3 msec up ramp and down ramp) at 500 Hz and 1,000 Hz. Do this by specifying a sine wave of the desired frequency with a gradual ramp up to full amplitude, followed by a down ramp at the end of the tone. Save the sine wave as an auditory file. Test the volume of each tone with a sound pressure level meter to verify that it is played at 60 dB. If speakers are used to present auditory stimuli, the sound should be tested at 60 cm away from the screen (where the participant will sit). If headphones will be used, measure the volume directly next to each headphone. 
	NOTE: It is easier to keep the computer at a standard volume and adjust the volume of the tone accordingly by adjusting the code used to generate the stimulus or an audio editing program.</li>
	<li>Create visual stimuli by either specifying the size and location of the flash in the experiment code, or by generating a JPEG or bitmap image with a black background and a white ring centered around a fixation crosshairs, and displaying at the appropriate time. Set the duration of the visual flash to 16 ms in the experiment code.</li>
	<li>Record speech stimuli by a native speaker in a quiet room against a plain white background from the shoulders up with the speaker in the center of the frame. Record the the video stimuli with the highest resolution video camera available. Alternatively, publicly available stimulus videos may be utilized if desired. 
	NOTE: Video and audio of the speaker saying the syllables &#8220;ba&#8221; and &#8220;ga&#8221; are required for this experiment.
	<ol>
		<li>Using any video editing program, export the auditory component of each track and save as a separate .wav file. Do this by going into export settings window and select &#8220;wav audio file&#8221; from the &#8220;Format&#8221; drop-down menu. Check &#8220;Export Audio&#8221; and then click &#8220;Export&#8221; to the bottom of the Export Settings window.&#160;</li>
		<li>Next, export the visual component (i.e., silent video) of each track and save as a separate .avi file. Do this by going into export settings window and select &#8220;Uncompressed AVI&#8221; from the &#8220;Format&#8221; drop-down menu. Check &#8220;Export Video&#8221; and then click &#8220;Export&#8221; to the bottom of the Export Settings window.</li>
		<li>Finally, remove the auditory component of the &#8220;ga&#8221; track and replace it with the auditory component of the &#8220;ba&#8221; track to make the McGurk stimulus. To do this select the &#8220;.avi&#8221; file from the desktop into the as the video source by selecting &#8220;Source&#8221;, in this case &#8220;ga_VOnly.avi&#8221;. Similarly select the other video &#8220;ba_Aonly.avi&#8221;. In the Program sequence menu, ensure that the video (V1) &#8220;Video 1&#8221; source is &#8220;ga_VOnly.avi&#8221;&#160;and the audio (A1) &#8220;Audio 1&#8221; source is &#8220;ba_Aonly.avi&#8221;.&#160;Verify that the onset of the visual stimulus &#8220;ga&#8221; is temporally aligned with the auditory stimulus &#8220;ba&#8221;. 
		NOTE: It is important that the auditory stimuli are the exact same recording in both the audiovisual and auditory only stimulus (not just the same syllable) so that the only difference between an audiovisual &#8220;ba&#8221; and the McGurk stimulus is the video component. This will ensure that one can make a proper comparison to examine the influence of the visual stimulus on the perceived auditory syllable.</li>
	</ol>
	</li>
</ol>
3. Task Battery
NOTE: This task requires that all participants are able to understand and comply with verbal instructions from the experimenter.
<ol>
	<li>Ensure that all participants have normal vision by conducting a simple screening prior to testing. Use a Snellen eye chart at 20 feet and ask the participant to read each line with both eyes open (participants will be viewing stimuli with both eyes open). Record the lowest line that participants accurately report the visual stimuli. Participants should have 20/40 vision or better.</li>
	<li>Ensure that all participants have normal hearing by testing hearing thresholds at 500, 1,000, 2,000, and 4,000 Hz in each ear. Auditory testing should be completed in a sound controlled room with an audiometer.
	<ol>
		<li>To find a participant&#8217;s threshold, instruct the participant to raise their hand each time they detect a tone. Play a pulsed 500 Hz tone routed to the right ear starting at 35 dB and decrease the volume in 5 dB steps. Once a participant no longer detects a tone, increase the volume in 5 dB steps to verify the lowest perceptible volume. Repeat this procedure with each frequency, and then repeat all tone frequencies in the left ear. Participants should have thresholds of 20 dB or lower.</li>
	</ol>
	</li>
	<li>Ensure that participants are able to understand and comply with verbal instructions by measuring both IQ and receptive language skills with standardized neuropsychological measures prior to testing. Participants should have a measured IQ of 70 or more. If desired, additional neuropsychological testing can be completed at this time.</li>
</ol>
4. Simultaneity Judgment (SJ)
NOTE: The SJ task is a two alternative forced-choice task (2-AFC) and consists of a visual ring and 1,000 Hz auditory tone presented at various SOAs (negative = auditory preceding visual, positive = visual proceeding auditory) presented in random order.
<ol>
	<li>Be sure to include fairly large SOAs (at least -400 to +400 msec) to get an accurate measurement of the full width of the TBW (typical stimulus set: -400, -300, -200, -150, -100, -50, 0, 50, 100, 150, 200, 300, 400 msec SOA). Use the same set of SOAs for each participant, which allows for easier comparison of task performance across participants. Present a minimum of 20 trials per SOA for a precise estimate. The task takes approximately 15 - 20 min to complete. Provide a short break every 100 trials to reduce participant fatigue.</li>
	<li>Instruct the participant to observe a flash and a beep and explain that their task is to decide if the flash and beep occurred at the same time or at different times. Instruct the participant to press &#8220;1&#8221; on the number pad, if the stimuli occurred at the same time, or &#8220;2&#8221;, if the stimuli occurred at a different time. 
	NOTE: If a response box is available, this may also be used for collecting responses. Include these same instructions on the response screen after each trial.</li>
	<li>As an alternative substitute the flash and beep with a visual and auditory speech token (mouthed &#8220;ba&#8221; and voiced &#8220;ba&#8221;) and present at the same SOAs with the same task instruction (&#8220;Same time or different time?&#8221;). In this manner, compare the TBW for stimuli varying in complexity and social content within individual subjects27.</li>
</ol>
5. Temporal Order Judgment (TOJ)
NOTE: The auditory TOJ task is a 2-AFC task used to examine the temporal acuity of auditory processing. The visual TOJ task is a 2-AFC task used to examine the temporal acuity of visual processing. The multisensory TOJ task is a 2-AFC task used to examine temporal acuity across audition and vision. Each task takes approximately 10 - 15 min to complete.
<ol>
	<li>In the auditory TOJ task, instruct the participant to listen to two beeps presented (500 Hz and 1,000 Hz) at various delays and ask the participant to press &#8220;1&#8221; if the higher tone is played first or press &#8220;2&#8221; if the lower tone is played first. Present 20 trials for each SOA in random order. 
	NOTE: Compared to the SJ task, there is a much smaller dynamic range of SOAs over which perception of unisensory auditory and visual temporal order changes, therefore use a stimulus set where smaller SOAs are more heavily represented (typical stimulus set: -250, -200, -150, -75, -50, -35, -20, -10, 10, 20, 35, 50, 75, 150, 200, 250 msec SOA, where negative = higher tone preceding lower tone, positive = lower tone proceeding higher tone) for the unisensory TOJ tasks.</li>
	<li>In the visual TOJ task, instruct the participant to observe two circles (above and below a central fixation crosshair) at various delays and ask the participant to press &#8220;1&#8221; if the top circle appears first or press &#8220;2&#8221; if the bottom circle appears first. Present 20 trials for each SOA in random order. 
	NOTE: In this task, negative SOAs indicate that the top circle was presented first and positive SOAs indicate that the bottom circle was presented first.</li>
	<li>In the audiovisual TOJ task, instruct the participant to observe a small central flash and listen to a single tone (1,000 Hz) at various delays and ask the participant to press &#8220;1&#8221;, if the beep was presented first or press &#8220;2&#8221; if the flash was presented first. Present 20 trials for each SOA in random order. 
	NOTE: Accuracy in the audiovisual TOJ is typically much worse compared to the unisensory auditory TOJ and visual TOJ tasks. This requires a wider range of SOAs compared to the unisensory TOJ tasks (typical stimulus set: -300, -250, -200, -150, -100, -80, -50, -20, 0, 20, 50, 80, 100, 150, 200, 250, 300). In this task, negative SOAs indicate that the auditory was presented first and positive SOAs indicated that the visual was presented first. 
	NOTE: As with the SJ task, the TOJ task can be adapted to examine temporal processing across multiple kinds of stimuli. Here the TOJ task was completed with simple stimuli (auditory beeps and visual flashes), but this can be expanded to look at other stimulus pairs like speech and biological motion24.</li>
</ol>
6. McGurk Task
NOTE: The McGurk illusion consists of a video of the visual syllable &#8220;ga&#8221; paired with an auditory recording of the syllable &#8220;ba&#8221;. Many subjects will actually fuse the visual and auditory syllables and perceive this pair as the syllable &#8220;da&#8221; or &#8220;tha&#8221;32.
<ol>
	<li>Instruct the participant to observe different syllables and ask the participant to report the syllable that they perceived. In one block present 20 trials each of the unisensory syllables (auditory only syllables (A-&#8220;ba&#8221;, A-&#8220;ga&#8221;) and visual only syllables (V-&#8220;ba&#8221;, V-&#8220;ga&#8221;) in random order. In a second block, present 20 trials each of the audiovisual syllables (AV-&#8220;ba&#8221;, AV-&#8220;ga&#8221;, and the A-&#8220;ba&#8221;/V-&#8220;ga&#8221; McGurk stimulus) in random order. Ask the participant to press the letter on the keyboard corresponding to the perceived syllable (&#8220;press b for ba, press g for ga, press d for da, press t for tha&#8221;). This task takes approximately 5 - 10 min total to complete.</li>
	<li>A more conservative estimate consists of an open response format33 in which the participant reports out loud the perceived syllable and the response is recorded by the experimenter.</li>
</ol>

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<li>Irwin, J. R., Tornatore, L. A., Brancazio, L., Whalen, D. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Can+children+with+autism+spectrum+disorders+%27hear%27+a+speaking+face%5BTitle%5D)+AND+%22Child+Dev%22%5BJournal%5D)">Can children with autism spectrum disorders 'hear' a speaking face.</a> Child Dev. 82 (5), 1397-1403 (2011).</li>
<li>Woynaroski, T. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Multisensory+Speech+Perception+in+Children+with+Autism+Spectrum+Disorders%5BTitle%5D)+AND+%22J+Autism+Dev+Disord%22%5BJournal%5D)">Multisensory Speech Perception in Children with Autism Spectrum Disorders.</a> J Autism Dev Disord. 43 (12), 2891-2902 (2013).</li>
<li>Magnotti, J. F., Beauchamp, M. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+Noisy+Encoding+of+Disparity+Model+of+the+McGurk+Effect%5BTitle%5D)+AND+%22Psychonomic+Bulletin+%26+Review%22%5BJournal%5D)">The Noisy Encoding of Disparity Model of the McGurk Effect.</a> Psychonomic Bulletin & Review. , (2014).</li>
<li>Hillock-Dunn, A., Wallace, M. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Developmental+changes+in+the+multisensory+temporal+binding+window+persist+into+adolescence%5BTitle%5D)+AND+%22Dev+Sci%22%5BJournal%5D)">Developmental changes in the multisensory temporal binding window persist into adolescence.</a> Dev Sci. 15 (5), 688-696 (2012).</li>
</ol>

The authors declare that they have no competing financial interests.

The manuscript describes elements of a psychophysical task battery that are used to assess temporal processing and acuity in sensory and multisensory systems research. The battery has wide applicability for a number of populations and has been used by our laboratory in order to characterize audiovisual temporal performance in typical adults18, children10,39, and in children and adults with autism17,23. In addition, it has been used to examine how various facets of the battery relate to one another in correlational analyses27, and is currently being used to relate sensory and multisensory performance measures to cognitive domains including language and communication, attention and executive function. It is important to note that the main limitation of this task battery with regards to testing individuals with ASD is that the format of the tasks requires that participants have the receptive language skills to understand verbal instructions and indicate this understanding. As such, the task battery is currently only suitable for testing high-functioning individuals with ASD.
The emphasis of the battery on temporal factors is grounded in the importance of these factors for the construction of veridical sensory and perceptual representations. In the multisensory realm, this is best captured in the construct of a multisensory &#8220;temporal binding window (TBW),&#8221; the epoch of time in which auditory and visual cues can strongly influence one another. As previously suggested, this window is a highly ecological construct, in that sensory events and their associated energies happen at different distances. Thus, accounting for the differences in propagation times of the auditory and visual signals, the brain assesses audiovisual temporal structure in relation to this window, and thus makes a probabilistic judgment as to whether the stimuli belong together or not. These data strongly argue for the TBW as a measure of temporal acuity and strength of multisensory integration, and indeed it has been shown that the width of this window appears to be correlated with the magnitude of the binding process, with those with smaller windows having larger indices of integration18,27.
In addition to be a probabilistic construct across individuals, the TBW is also very much dependent on stimulus and task. Indeed, as highlighted in the battery presented here, multisensory temporal function can be assessed using stimuli ranging from the very simple and non-ecological (e.g., flashes and beeps) to the most ethologically relevant of audiovisual signals (i.e., speech). In addition, the TBW can be derived from measures including simultaneity judgments, temporal order judgments, perception of illusory stimuli, etc. Hence, the collective use of tasks that differ in both their stimulus and task contingencies provide the most comprehensive window into audiovisual temporal function.
An individual&#8217;s TBW is measured by extracting parameters from a curve fit to the participant&#8217;s raw performance from the SJ task. Therefore, care should be taken to examine individual subjects&#8217; curve fits to ensure that the fitted curve accurately describes the raw data. Although an array of definitions for measuring the width of the TBW exists in the literature, it is suggested that the following criteria be used to easily compare across subjects while still capturing individual differences in performance. First, the &#8220;left&#8221; and &#8220;right&#8221; TBW should be measured from 0 msec (objectively auditory leading asynchrony vs. visual leading asynchrony) as opposed to the individual PSS (the mean of the fitted curve). Secondly, the width should be measured at 50% report of synchronous trials (not 50% of the maximum response for that subject), capturing the range of asynchronies in which a subject reported &#8220;same time&#8221; for a majority of trials. Because some subjects never report &#8220;same time&#8221; for more than 75% of the trials on any SOA, this will allow the greatest number of subjects to be included in the analysis.
Along with its utility in characterizing multisensory temporal function in &#8220;neurotypical&#8221; populations across the lifespan, elements of the described task battery have been used to assess sensory and multisensory processes in individuals with ASD26-28,37. Although sensory disturbances have been classically associated with autism, it is only recently that these disturbances have entered the diagnostic vernacular, and that a stronger appreciation of how altered multisensory function may contribute to the autism phenotype has been gained. Indeed, the core impacted domains in autism (i.e., social communication) are representations that are built on the basis of multisensory processes, strongly suggesting that alterations in these processes could have detrimental effects on social communication. Using elements of the temporal battery described here, it has been established that multisensory temporal acuity is poorer in autism, and that this poorer performance is related to speech comprehension measures28. Ongoing work is seeking to relate various aspects of audiovisual temporal performance to a host of cognitive measures.

Traditional neuroscience research has often approached understanding sensory perception by focusing on the individual sensory modalities. However, the environment consists of a wide array of sensory inputs that are integrated into a unified perceptual view of the world in a seemingly effortless manner. The fact that we exist in such a rich multisensory environment requires that we better understand the way in which the brain combines information across the different sensory systems. The need for this understanding is further amplified by the fact that the presence of multiple pieces of sensory information often results in substantial improvements in behavior and perception1-3. For example, there is a large improvement (up to 15 dB in the signal-to-noise ratio) in the ability to understand speech in a noisy environment if the observer can also see the speaker&#8217;s lip movements4-7.
One of the major factors that affects how the different sensory inputs are combined and integrated is their relative temporal proximity. If two sensory cues occur close together in time, a temporal structure that suggests common origin, they are highly likely to be integrated as evidenced by changes in behavior and perception8-12. One of the most powerful experimental tools for examining the impact of multisensory temporal structure on behavioral and perceptual responses is simultaneity judgment (SJ) tasks13-16. In such a task, multisensory (e.g., visual and auditory) stimuli are paired at various stimulus onset asynchronies (SOAs) ranging from objectively simultaneous (i.e., a temporal offset of 0 msec) to highly asynchronous (e.g., 400 msec). Participants are asked to judge the stimuli as simultaneous or not via a simple button press. In such a task, even when the visual and auditory stimuli are presented at SOAs of 100 msec or more, subjects report that the pair was simultaneous on a large proportion of trials. The window of time in which two inputs can occur and have a high probability of being perceived as occurring simultaneously is known as the temporal binding window (TBW)17-19.
The TBW is a highly ethological construct, in that it represents the statistical regularities of the world around us19. The &#8220;window&#8221; provides flexibility for the specification of events of common origin; one that allows for stimuli occurring at different distances with different propagation times (both physical and neural) to still be &#8220;bound&#8221; to one another. However, although the TBW is a probabilistic construct, changes that expand (or contract) the size of this window are likely to have cascading and potentially detrimental effects on perception20,21.
Autism spectrum disorder (ASD) is a neurodevelopmental disorder that has been classically diagnosed on the basis of deficits in social communication and the presence of restricted interests and repetitive behaviors22. In addition, and as recently codified in the DSM-5, children with ASD frequently exhibit alterations in their responses to sensory stimuli. Rather than being restricted to a single sense, these deficits often encompass multiple senses including hearing, touch, balance, taste and vision. Along with such a &#8220;multisensory&#8221; presentation, individuals with ASD often exhibit deficits in the temporal realm. Collectively, these observations suggest that multisensory temporal function may be preferentially altered in autism17,23-25. Although concordant with the view of altered sensory function in ASD, changes in multisensory temporal function may also be an important contributor to the deficits in social communication in ASD, given the importance of rapid and accurate binding of multisensory stimuli for social and communication functions. Take as an example the speech exchange described above in which important information is contained in both the auditory and visual modalities. Indeed, these tasks have been used to demonstrate significant differences in the width of the multisensory TBW in high functioning children with autism26-28.
Due to its importance for normal perceptual function, its potential implications for higher order processes such as social communication (and other cognitive abilities), and its clinical relevance, a battery of tasks designed to assess multisensory temporal function in children with ASD is described.

<table><tbody><tr><td>Oscilloscope</td><td></td><td></td><td></td></tr><tr><td>Photovoltaic cell</td><td></td><td></td><td></td></tr><tr><td>Microphone</td><td></td><td></td><td></td></tr><tr><td>Noise-cancelling headphones</td><td></td><td></td><td></td></tr><tr><td>Chin rest</td><td></td><td></td><td></td></tr><tr><td>Audiometer</td><td></td><td></td><td></td></tr></tbody></table>

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.

This task battery has proven very successful in measuring individual differences in temporal processing in individuals with and without ASD17,18,23,27. For the SJ task, plot the resulting data from each individual subject by first calculating the proportion of responses at each SOA that subject responded &#8220;synchronous&#8221; and then fitting the resulting response curve with a Gaussian curve. As illustrated in Figure 1A, there is a window of time in which visual-auditory stimuli pairs can be presented with a delay and will be perceived as synchronous on a high proportion of trials. The width of the &#8220;left&#8221; (covering auditory-first asynchronies) and &#8220;right&#8221; (covering visual-first asynchronies) side of the TBW is measured by calculating the width of the window from 0 ms to the SOA on each side that corresponds to 50% synchronous responses (dashed lines, Figure 1A). A robust finding across both TD participants and clinical populations is that the right TBW (visual first) is typically wider than the left (auditory first) TBW. Participants with ASD also show a wider TBW than their TD counterparts (Figure 1B).
For the TOJ tasks, the data from each individual subject is first plotted by calculating the proportion of responses at each SOA that the &#8220;positive&#8221; stimulus was perceived as being presented first (higher tone, bottom circle, visual flash), and the resulting response curves from each task are fit with a cumulative Gaussian curve. Example TOJ curves from a single TD subject are shown in Figure 2. While performance on the unisensory TOJ tasks is highly accurate for all but the smallest SOAs (2A and 2B), determining temporal order across modalities is much more difficult, as indexed by a much more shallow curve (2C) and decreased accuracy (2D) for the multisensory TOJ task. The point of subjective simultaneity (PSS) for each subject is measured by calculating the SOA at which subjects perform at chance (see dashed line, Figure 2A-C). Perform a t-test to determine if there are differences between groups. To compare performance across tasks or across subjects, calculate accuracy at each SOA and plot as a function of the delay between the stimulus pair (collapsing across the positive and negative SOA at each delay; see Figure 2D). Some studies examining sensory processing in ASD have found differences in TOJ tasks between ASD and TD groups23,34, while others have not observed significant differences between groups27. The reason for these discrepancies is unclear, although high heterogeneity across individuals with ASD35 and slight differences in task structure across these studies may play a role.
McGurk perception is analyzed by calculating the proportion of trials that the participant perceived the fused percept &#8220;da&#8221; compared to the total number of trials presented. Example results from the McGurk task are shown for an ASD and TD subject group in Figure 3A. Even within the same individual, responses to the stimulus can often vary from trial-to-trial, therefore it is useful to consider the distribution of these responses. There is currently some debate in the literature about differences in multisensory integration as indexed by McGurk perception. Some groups have found that TD subjects have increased McGurk perception compared with ASD subjects27,36, while others have found that ASD subjects had higher McGurk perception37. Some of these discrepancies may be explained by differences in the McGurk stimulus used in each study. Some McGurk stimuli are &#8220;stronger&#8221; than others (i.e., they are more likely to elicit the illusory McGurk percept on a high proportion of trials for a subject) than others, which can be quantified by a recent model of variability McGurk perception38. As an example of the utility of this battery, individual differences in temporal processing (such as the width of the TBW) can be correlated with performance differences on a perceptual task like the McGurk illusion (Figure 3B). Several studies have observed a link between temporal acuity in the SJ task and perceptual differences in speech perception in the McGurk task and other measures of multisensory integration18,27.
<img alt="Figure 1" src="/files/ftp_upload/52677/52677fig1highres.jpg" width="700" /> 
Figure 1. Simultaneity Judgment (SJ) results. Representative data from the Simultaneity Judgment (SJ) task for a single ASD subject (age = 8) and a single TD subject (age = 9). (A) Raw data from the SJ task for a single ASD subject is shown in black. The fitted Gaussian curve is shown in blue. The blue dashed lines show width of the left and right TBW (227 ms and 333 ms, respectively) for this individual subject. (B) Fitted TBW curves for the same ASD subject in blue and a single TD subject is shown in red. The TD subject has a smaller TBW (left TBW = 166 msec, right TBW = 196 msec) than the ASD subject. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/52677/52677fig1highres.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" src="/files/ftp_upload/52677/52677fig2highres.jpg" width="700" /> 
Figure 2. Temporal Order Judgment (TOJ) results. Representative data from the Temporal Order Judgment (TOJ) tasks from a single TD subject (age = 15). (A) Raw data and fitted curve for auditory TOJ task. Data are plotted as a function of lower pitch first responses across the different SOAs (negative SOAs indicate higher pitch came first, positive SOAs indicate lower pitch came first). (B) Raw data and fitted curve for visual TOJ task. Data are plotted as a function of bottom circle first responses across the SOAs (negative SOAs indicate top circle came first, positive SOAs indicate bottom circle came first). (C) Raw data and fitted curve for multisensory TOJ. Data are plotted as a function of visual flash first responses across the SOAs (negative indicates auditory beep came first, positive SOAs indicate visual flash came first). (D) Same data from A-C plotted as the average accuracy (correct identification of temporal order) at each delay (collapsed across the negative and positive SOA). <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/52677/52677fig2highres.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" src="/files/ftp_upload/52677/52677fig3highres.jpg" width="700" /> 
Figure 3. McGurk Task results and comparison of McGurk performance with Simultaneity Judgment performance. Representative data from the McGurk task with ASD and TD subject groups, adapted with permission from27. (A) Responses to the McGurk stimulus for TD (shown in black) and ASD (shown in red) subjects. Because of the variability of responses for the same stimulus both within individual subjects and across subjects in a group, responses are shown as the percent of trials that were perceived as each phoneme. ASD subjects heard the auditory syllable &#8220;ba&#8221; on a larger percentage of trials than TD subjects, while the TD subjects heard the fused audiovisual syllable &#8220;da&#8221; on a larger percentage of trials than ASD subjects. (B) Correlation between the width of the temporal binding window (TBW) from the SJ task and the proportion of trials in which the fused audiovisual syllable &#8220;da&#8221; was perceived from the McGurk stimulus in the same group of ASD subjects. There was a significant negative correlation where the low McGurk perception was correlated with a larger TBW (r = 0.46, p &#60; 0.05). <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/52677/52677fig3highres.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Testing Sensory and Multisensory Function in Children with Autism Spectrum Disorder at JoVE.com

Testing Sensory and Multisensory Function in Children with Autism Spectrum Disorder

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 ...

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Nanyang Technological University

Research

JoVE Journal

Behavior

16.5K Views.  Vanderbilt University Medical Center. 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.

Video: Testing Sensory and Multisensory Function in Children with Autism Spectrum Disorder

Quantitative Assessment of Cortical Auditory-tactile Processing in Children with Disabilities

Objective and easy measurement of sensory processing is extremely difficult in nonverbal or vulnerable pediatric patients. We developed a new methodology to quantitatively assess children&#39;s cortical processing of light touch, speech sounds and the multisensory processing of the 2 stimuli, without requiring active subject participation or causing children discomfort. To accomplish this we developed a dual channel, time and strength calibrated air puff stimulator that allows both tactile stimulation and sham control. We combined this with the use of event-related potential methodology to allow for high temporal resolution of signals from the primary and secondary somatosensory cortices as well as higher order processing. This methodology also allowed us to measure a multisensory response to auditory-tactile stimulation.

Objective and easy measurement of sensory processing is extremely difficult in nonverbal or vulnerable pediatric patients. We developed a new methodology to quantitatively assess infants and children&#39;s cortical processing of light touch, speech sounds, and the multisensory processing of the 2 stimuli, without requiring active subject participation or causing discomfort in vulnerable patients.

Objective and easy measurement of sensory processing is extremely difficult in nonverbal or vulnerable pediatric patients. We developed a new methodology ...

A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants

Understanding typical and atypical development remains one of the fundamental questions in developmental human neuroscience. Traditionally, experimental paradigms and analysis tools have been limited to constrained laboratory tasks and contexts due to technical limitations imposed by the available set of measuring and analysis techniques and the age of the subjects. These limitations severely limit the study of developmental neural dynamics and associated neural networks engaged in cognition, perception and action in infants performing &#8220;in action and in context&#8221;. This protocol presents a novel approach to study infants and young children as they freely organize their own behavior, and its consequences in a complex, partly unpredictable and highly dynamic environment. The proposed methodology integrates synchronized high-density active scalp electroencephalography (EEG), inertial measurement units (IMUs), video recording and behavioral analysis to capture brain activity and movement non-invasively in freely-behaving infants. This setup allows for the study of neural network dynamics in the developing brain, in action and context, as these networks are recruited during goal-oriented, exploration and social interaction tasks.

This protocol presents a novel methodology for the neural decoding of intent from freely-behaving infants during unscripted social interaction with an actor. Neural activity is acquired using non-invasive high-density active scalp electroencephalography (EEG). Kinematic data is collected with inertial measurement units and supplemented with synchronized video recording.

Understanding typical and atypical development remains one of the fundamental questions in developmental human neuroscience. Traditionally, experimental ...

Eye Tracking Young Children with Autism

The rise of accessible commercial eye-tracking systems has fueled a rapid increase in their use in psychological and psychiatric research. By providing a direct, detailed and objective measure of gaze behavior, eye-tracking has become a valuable tool for examining abnormal perceptual strategies in clinical populations and has been used to identify disorder-specific characteristics1, promote early identification2, and inform treatment3. In particular, investigators of autism spectrum disorders (ASD) have benefited from integrating eye-tracking into their research paradigms4-7. Eye-tracking has largely been used in these studies to reveal mechanisms underlying impaired task performance8 and abnormal brain functioning9, particularly during the processing of social information1,10-11. While older children and adults with ASD comprise the preponderance of research in this area, eye-tracking may be especially useful for studying young children with the disorder as it offers a non-invasive tool for assessing and quantifying early-emerging developmental abnormalities2,12-13. Implementing eye-tracking with young children with ASD, however, is associated with a number of unique challenges, including issues with compliant behavior resulting from specific task demands and disorder-related psychosocial considerations. In this protocol, we detail methodological considerations for optimizing research design, data acquisition and psychometric analysis while eye-tracking young children with ASD. The provided recommendations are also designed to be more broadly applicable for eye-tracking children with other developmental disabilities. By offering guidelines for best practices in these areas based upon lessons derived from our own work, we hope to help other investigators make sound research design and analysis choices while avoiding common pitfalls that can compromise data acquisition while eye-tracking young children with ASD or other developmental difficulties.

Eye tracking has long been used to study gaze patterns in typically-developing individuals, but recent technological advancements have made its use with clinical populations, including autism, more feasible. While eye-tracking young children with autism can offer insight into early symptom manifestations, it involves methodological challenges. Suggestions for best practices are provided.

The rise of accessible commercial eye-tracking systems has fueled a rapid increase in their use in psychological and psychiatric research. By providing a ...

Medicine

Portable Intermodal Preferential Looking (IPL): Investigating Language Comprehension in Typically Developing Toddlers and Young Children with Autism

One of the defining characteristics of autism spectrum disorder (ASD) is difficulty with language and communication.1 Children with ASD's onset of speaking is usually delayed, and many children with ASD consistently produce language less frequently and of lower lexical and grammatical complexity than their typically developing (TD) peers.6,8,12,23 However, children with ASD also exhibit a significant social deficit, and researchers and clinicians continue to debate the extent to which the deficits in social interaction account for or contribute to the deficits in language production.5,14,19,25
Standardized assessments of language in children with ASD usually do include a comprehension component; however, many such comprehension tasks assess just one aspect of language (e.g., vocabulary),5 or include a significant motor component (e.g., pointing, act-out), and/or require children to deliberately choose between a number of alternatives. These last two behaviors are known to also be challenging to children with ASD.7,12,13,16
We present a method which can assess the language comprehension of young typically developing children (9-36 months) and children with autism.2,4,9,11,22 This method, Portable Intermodal Preferential Looking (P-IPL), projects side-by-side video images from a laptop onto a portable screen. The video images are paired first with a 'baseline' (nondirecting) audio, and then presented again paired with a 'test' linguistic audio that matches only one of the video images. Children's eye movements while watching the video are filmed and later coded. Children who understand the linguistic audio will look more quickly to, and longer at, the video that matches the linguistic audio.2,4,11,18,22,26
This paradigm includes a number of components that have recently been miniaturized (projector, camcorder, digitizer) to enable portability and easy setup in children's homes. This is a crucial point for assessing young children with ASD, who are frequently uncomfortable in new (e.g., laboratory) settings. Videos can be created to assess a wide range of specific components of linguistic knowledge, such as Subject-Verb-Object word order, wh-questions, and tense/aspect suffixes on verbs; videos can also assess principles of word learning such as a noun bias, a shape bias, and syntactic bootstrapping.10,14,17,21,24 Videos include characters and speech that are visually and acoustically salient and well tolerated by children with ASD.

Portable Intermodal Preferential Looking IPL: Investigating Language Comprehension in Typically Developing Toddlers and Young Children with Autism

A reliable home-based way to assess the language comprehension of very young typically developing children, as well as those with autism, is described. The method analyzes children's eye gaze while viewing side-by-side images but hearing an audio that matches only one image. Stimuli are designed with young participants in mind.

One  of the defining characteristics of autism spectrum disorder (ASD) is difficulty  with language and communication.1  Children with ASD's onset of ...

An Electrophysiology Protocol to Measure Reward Anticipation and Processing in Children

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

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

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

Using the Visual World Paradigm to Study Sentence Comprehension in Mandarin-Speaking Children with Autism

Sentence comprehension relies on the ability to rapidly integrate different types of linguistic and non-linguistic information. However, there is currently a paucity of research exploring how preschool children with autism understand sentences using different types of cues. The mechanisms underlying sentence comprehension remains largely unclear. The present study presents a protocol to examine the sentence comprehension abilities of preschool children with autism. More specifically, a visual world paradigm of eye-tracking is used to explore the moment-to-moment sentence comprehension in the children. The paradigm has multiple advantages. First, it is sensitive to the time course of sentence comprehension and thus can provide rich information about how sentence comprehension unfolds over time. Second, it requires minimal task and communication demands, so it is ideal for testing children with autism. To further minimize the computational burden of children, the present study measures eye movements that arise as automatic responses to linguistic input rather than measuring eye movements that accompany conscious responses to spoken instructions.

We present a protocol to examine the use of morphological cues during real-time sentence comprehension by children with autism.

Sentence comprehension relies on the ability to rapidly integrate different types of linguistic and non-linguistic information. However, there is ...

Comparing Eye-tracking Data of Children with High-functioning ASD, Comorbid ADHD, and of a Control Watching Social Videos

Children with autism spectrum disorders (ASD) are known to have sensory-perceptual processing deficits that weaken their abilities to attend and perceive social stimuli in daily living contexts. Since daily social episodes consist of subtle dynamic changes in social information, any failure to attend to or process subtle human nonverbal cues, such as facial expression, postures, and gestures, might lead to inappropriate social interaction. Traditional behavioral rating scales or assessment tools based on static social scenes have limitations in capturing the moment-to-moment changes in social scenarios. An eye-tracking assessment, which can be administered in a video-based mode, is therefore preferred, to augment clinical observation. In this study, using the single-case comparison design, the eye-tracking data of three participants, a child with autism spectrum disorder (ASD), another with comorbid attention deficit-hyperactive disorder (ADHD), and a neurotypical control, are captured while they view a video of social scenarios. The eye-tracking experiment has helped answer the research question: How does social attention differ between the three participants? By predefining areas of interest (AOIs), their visual attention on relevant or irrelevant social stimuli, how fast each participant attends to the first social stimuli appearing in the videos, for how long each participant continues to attend to those stimuli within the AOIs, and the gaze shifts between multiple social stimuli appearing concurrently in the same social scene are captured, compared, and analyzed in a video-based eye-tracking experiment.

This is a qualitative comparative case study analysis of eye-tracking data on the first moments of social video scenes as viewed by three participants: one with autism spectrum disorder, one with comorbid attention deficit-hyperactive disorder, and one neurotypical control.

Children with autism spectrum disorders (ASD) are known to have sensory-perceptual processing deficits that weaken their abilities to attend and perceive ...

A Familiarization Protocol Facilitates the Participation of Children with ASD in Electrophysiological Research

This paper includes a detailed description of a familiarization protocol, which is used as an integral component of a larger research protocol to collect electroencephalography (EEG) data and Event-Related Potentials (ERPs). At present, the systems available for the collection of high-quality EEG/ERP data make significant demands on children with developmental disabilities, such as those with an Autism Spectrum Disorder (ASD). Children with ASD may have difficulty adapting to novel situations, tolerating uncomfortable sensory stimuli, and sitting quietly. This familiarization protocol uses Evidence-Based Practices (EBPs) to increase research participants&#39; knowledge and understanding of the specific activities and steps of the research protocol. The tools in this familiarization protocol are a social narrative, a visual schedule, the Premack principle, role-playing, and modeling. The goal of this familiarization protocol is to increase understanding and agency and to potentially reduce anxiety for child participants, resulting in a greater likelihood of the successful completion of the research protocol for the collection of EEG/ERP data.

Electrophysiological research is an important tool for identifying biomarkers of developmental disorders, including Autism Spectrum Disorders (ASD), but data collection in these populations remains challenging. This work presents a familiarization protocol to accompany research that includes electroencephalography (EEG) to improve the likelihood of collecting EEG data from children with ASD.

This paper includes a detailed description of a familiarization protocol, which is used as an integral component of a larger research protocol to collect ...

Neuroscience

Executive Function in Autism Spectrum Disorder

Source: Laboratories of Jonas T. Kaplan and Sarah I. Gimbel&#8212;University of Southern California
Attention, working-memory, planning, impulse control, inhibition, and mental flexibility are important components of human cognition that are often referred to as executive functions. Autism spectrum disorder is a developmental disorder that is characterized by impairments in social interaction, communication, and repetitive behaviors. It is a disorder that lasts a lifetime, and is thought to affect 0.6% of the population. The symptoms of autism suggest a deficit in executive function, which may be assessed by specialized neuropsychological tests. By employing several tests that each emphasize different aspects of executive function, we can gain a more complete picture of the cognitive profile of the disorder. 
One such task, known as the Wisconsin Card Sorting Test (WCST), is a cognitively complex task used widely in research and clinical studies as a highly sensitive measure of deficits in executive function. It tests a person's ability to shift attention and tests their flexibility with changing rules and reinforcement.1 In the WCST, a participant is presented with four stimulus cards, incorporating three stimulus parameters: color, shape, and number. The participant is asked to sort response cards according to different principles, changing their sorting criteria based on feedback from the experimenter. Participants try out different rules until they find the correct method for sorting the cards. Patients with executive dysfunction tend to get stuck in the card sorting task, unable to change their sorting strategy. This persistence with an incorrect strategy is called perseveration. 
A second task, The Tower of London (ToL) is a test dependent on complex planning, re-evaluation, and updating of planned moves. Individuals with autism have been reported to be impaired on tasks involving planning.2 In the ToL task, individuals must move disks from a prearranged sequence on three pegs to match a goal state in as few moves as possible, following specific rules. 
A third task, known as the Stroop test, targets cognitive inhibition. In this task participants are shown a name of a color, written in a different color, and are asked to identify the color the word is written in. For example, in an incongruent condition, the word blue would be written in green. Individuals with inhibition difficulty should not perform as well as typically developing individuals on this task involving inhibition of the written word.
In this video, we show how to administer the WCST, ToL, and Stroop task to compare flexibility, planning, and inhibition in children with autism spectrum disorder and typically developing counterparts, and explore how each of these groups performs on these different aspects of executive function.

Behavioral Tests to Assess Executive Functions in Children with ASD

Source: Laboratories of Jonas T. Kaplan and Sarah I. Gimbel&#8212;University of Southern California
Attention, working-memory, planning, impulse control, ...

Education

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Psychology

Neuropsychology

Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental condition marked by persistent deficits in social communication and interaction alongside restrictive and repetitive behaviors or interests. ASD is sometimes accompanied by intellectual impairment.
These core symptoms manifest differently among individuals, ranging from mild to severe. The disorder&#39;s complexity extends beyond its clinical presentation, encompassing a diverse range of biological, cognitive, and sociocultural influences.
Early Signs and Diagnosis
Early indicators of ASD typically emerge within the first two years of life. Children with ASD often display limited responsiveness to social stimuli, such as reduced eye contact or lack of reaction to their name being called. Difficulties with joint attention &#8212; a shared focus between an individual and another person &#8212; are common. Repetitive behaviors, including hand-flapping, rocking, or fixation on particular objects or routines, provide additional diagnostic clues. Despite advances in diagnostic criteria, disparities persist across demographic groups, influenced by socioeconomic, ethnic, and gender biases. Girls, for instance, may exhibit subtler symptoms, complicating timely recognition.
Etiology and Contributing Factors
ASD is a multifactorial condition with a substantial genetic basis. Children whose siblings have ASD are at increased risk for the disorder. Twin studies reveal concordance rates upwards of 80% in monozygotic twins, highlighting hereditary influences. Variations in genes related to synaptic function and neural development are implicated. Environmental contributors, such as advanced parental age, prenatal exposure to certain medications or infections, and other perinatal factors, interact with genetic predispositions. Neurologically, alterations in brain connectivity, structure, and neurotransmitter systems further underlie ASD pathophysiology.
Cognitive and Sensory Processes
Psychological theories underscore deficits in cognitive processes, such as the theory of mind &#8212; the ability to attribute mental states to oneself and others &#8212; as central to ASD. Individuals with ASD may struggle to interpret others&#39; intentions, leading to difficulties in social reciprocity. Sensory processing differences, including heightened sensitivity to sounds, lights, or textures, significantly affect daily experiences, often contributing to heightened anxiety or behavioral challenges. The social motivation approach to ASD suggests that individuals with ASD are profoundly less interested in social stimuli compared to typically developing people.
Importance of Early Intervention
Intervening early in a child&#39;s developmental trajectory is vital for optimizing outcomes. Evidence-based approaches, including applied behavior analysis (ABA), speech therapy, and occupational therapy, focus on enhancing communication, social engagement, and adaptive skills. Early interventions leverage the brain&#39;s plasticity during critical developmental windows, improving independence and quality of life for individuals with ASD.

Autism spectrum disorder, or ASD, is characterized by persistent difficulties in social communication and interaction, including reduced social bonding or ...