We would like to thank Jyoti Mishra for useful discussions regarding the paradigm. This research was supported by NIH grants R33DA026109 and R21MH096329 to MSC.

NOTE: This study protocol was developed in accordance with the ethical guidelines approved by the investigational review board at University of California Los Angles.
1. Preparation of Auditory and Visual Stimuli
<ol>
	<li>Using software in which visual images can be generated, create two gray scale sinusoid gratings, approximately 5.7 inches in diameter and of any frequency (e.g., 1.36 cycles/degree of visual angle). The images will have an on-screen duration of 100 msec.
	<ol>
		<li>Tilt one of the gratings about 10 visual degrees to the right off the median, and tilt the other grating the same amount to the left of the grating.</li>
		<li>Ensure that the degree of the tilt is sufficient to allow the participants to distinguish a left tilt from a right tilt without relying on guessing.</li>
	</ol>
	</li>
	<li>Using software in which auditory tones can be generated, create two pure tones of 100 msec duration.
	<ol>
		<li>Make one of the tones of a higher pitch and the other of a lower pitch. For instance, one pitch can be 750 Hz and the other 900 Hz.</li>
		<li>As for the visual stimuli, ensure that the tones are sufficiently distinct such that participants can distinguish between them without relying on guessing.</li>
	</ol>
	</li>
</ol>
2. Programming of Stimulus Presentation
<ol>
	<li>Using presentation software, create the computer code that will control the presentation of the auditory and visual stimuli during the experiment.
	<ol>
		<li>First select the number of stimuli to be presented. Present at least 150 of each of visual and auditory stimuli per experimental condition, to ensure that there are enough repetitions for a reliable neurophysiological response.</li>
		<li>Present visual stimuli centrally on a gray background, with the participant sitting at a comfortable viewing distance. Present the auditory stimuli through speakers positioned on either side of the screen. 
		Note: For visual stimuli we recommend a gray background, with RGB values at the mid-point (128,128,128) between pure white (255,255,255) and pure black (0,0,0), with the white and black used in generation of the sinusoid stimuli. This ensures that the mean brightness of the background and stimulus are comparable, and the contrast is constant between any point in the stimulus and the background.</li>
		<li>For each of auditory and visual stimuli, independently select the timing for the stimuli. 
		Note: This prevents participants from anticipating stimuli based on temporal relationships between the two streams.</li>
		<li>Use an inter-stimulus interval (ISIs) of approximately 1 sec between sequential presentations of stimuli from the same modality. Slower ISIs will make the task more demanding on vigilance, faster ISIs may make it impossible for participants to make their responses in time.</li>
		<li>Vary the precise ISI randomly within a range, such as 0.7 to 2 sec, to make the stimuli unpredictable to participants, preventing neural responses associated with anticipation.</li>
		<li>Because cross-modal interactions can arise from simultaneously or near-simultaneously presented stimuli 21,22, keep the ISI between stimuli from two different streams at no less than 300 msec.</li>
	</ol>
	</li>
	<li>Ensure that the auditory and visual stimuli appear to occur interleaved to the participants, but never co-occurring.</li>
	<li>Last, divide the stimuli into segments of twenty-five. These segments will be preceded by one of the three randomly selected task instructions, described in the next section.</li>
</ol>
3. Task Instruction
<ol>
	<li>Orient the participant to the task prior to collecting neurophysiological measures of brain activity.
	<ol>
		<li>Instruct participants to attend and respond to the auditory tones and to ignore the visual stimuli when the instruction is &#8220;Listen&#8221;. Present this instruction both through audio and visual means.</li>
		<li>Assign two buttons for participants to make responses to each tone. For example, &#8220;press the left arrow if the tone is high, and right arrow if the tone is low&#8221; when the instruction is &#8220;Listen&#8221;.</li>
		<li>Similarly, instruct participants to attend and respond to the visual gratings and to ignore the auditory stimuli when the instruction is &#8220;Look&#8221;.</li>
		<li>Assign two buttons for participants to make responses to the visual gratings. For example, &#8220;press the left arrow if the grating is tilted to the left, and right arrow if the grating is tilted to the left&#8221;.
		<ol>
			<li>Use the same two buttons for visual stimuli as for auditory stimuli to enhance the interference between the modalities and therefore the need to employ attention control mechanisms.</li>
		</ol>
		</li>
		<li>Finally, instruct participants to make no responses when the instruction is &#8220;Passive&#8221;, but ensure that participants keep their eyes open and focused on the screen.</li>
	</ol>
	</li>
	<li>Throughout the task session, alternate the instructions for &#8220;Listen&#8221; and &#8220;Look&#8221; between segments to switch a previously attended modality to being irrelevant, thus making it a potent distractor.</li>
	<li>Remind the participants to keep their eyes fixated on the middle of the screen, or a small dot or crosshair presented at the location of the visual stimulus, and to keep their eyes open throughout the experiment.</li>
	<li>Build in eight to ten second breaks between segments to mitigate effects of fatigue, allow the participants to rest their eyes, as well as longer 1-2 min breaks every 6-8 min.</li>
	<li>Finally, provide each participant with ample practice to ensure that they are performing the task correctly. It may be beneficial, especially for participants who have attention difficulties, to practice the visual and the auditory tasks with the attended stream presented in isolation, without the concurrent presentation of the distractor stream.</li>
</ol>
4. Neurophysiological Data Collection
<ol>
	<li>Once the participants are familiar with the task, begin collection of neurophysiological responses to attended and ignored signals during the IMAT.</li>
	<li>Prepare the electroencephalography (EEG) cap and recording equipment according to manufacturer instructions, and in accordance with current methodology and publication standards for EEG research 26,27. 
	Note: Important EEG recording parameters for EEG recording during the IMAT, that can be user specified, include: (a) sampling rate of 128-1,024 Hz, to capture the low-frequency of ERP signals; (b) alternating current (AC) recording to minimize slow drift; (c) net with sampling of entire scalp and with at minimum of 64 sensors, if source imaging analyses are to be performed.</li>
	<li>Apply the cap to the participant&#8217;s scalp and verify signal impedance and quality at each of the sensors. Pay special attention to ensure that impedances of the recording electrodes are uniform and within the range recommended by manufacturer. 
	Note: At this time, also add any additional physiological measurement devices if wanting to collect non-neural physiological signals such as respiration or pulse.</li>
	<li>Synchronize the neurophysiological recordings with the stimulus presentation software and neurophysiological recording software according to manufacturer&#8217;s instructions.</li>
	<li>Record the neurophysiological signals while the participant performs the task, ensuring that the recording software has precise record of the timing of each stimulus and response for subsequent analysis.</li>
</ol>
5. Offline Data Analysis
<ol>
	<li>Prepare the neurophysiological data for statistical analysis using analysis software.</li>
	<li>First, remove non-neural signal components that will contribute variability to the neurophysiological recordings of brain responses.
	<ol>
		<li>Use a high-pass filter of 0.1-1 Hz, to remove slow drifts such as those caused by changes in impedance of the sensors.</li>
		<li>Use a low-pass filter of 30-50 Hz to remove high frequency components introduced by electrical noise.</li>
		<li>Identify sensors that show unreliable data, and exclude these or interpolate the signals.</li>
		<li>Identify and eliminate large infrequent noise components such as muscle artefact from jaw contraction or movements of the forehead, and systematic, non-neural contributions, such as eye movements. 
		Note: Typical algorithms to remove non-neural components include independent components analysis and regression, as well as iterative algorithms based on explicit selection criteria (e.g., voltage changes that exceed a threshold). Follow guidelines of available analysis software, and proceed in accordance with current standards for EEG research 26,27.</li>
	</ol>
	</li>
	<li>Once major non-neural components of the neurophysiological data have been removed, re-reference the data at each electrode by subtracting from each sensor the mean across all other sensors or the mean across left and right mastoid channels. 
	Note: This step re-expresses the effects at each sensor relative to a neutral reference that is assumed to contain zero neural signals. 
	Note: Sparser electrode montages may not have sufficient sampling to meet the assumptions of this technique 26,27. In the latter case, the mean of the left and right mastoid may provide a more accurate reference.</li>
	<li>Next extract temporal epochs of approximately 1 sec surrounding each auditory and each visual event shown. Include 100 msec preceding the stimulus onset to serve as a baseline interval and at least 600 msec following the stimulus onset.</li>
	<li>Average the data from all epochs that fall into the same condition &#8212; attended, ignored, and passively perceived stimuli &#8212; to compute the average evoked response potential or &#8220;ERP&#8221;. Subtract the mean of the data in the pre-stimulus baseline to re-express the ERP amplitudes as changes relative to the pre-stimulus signal.</li>
	<li>To identify the time course of attending processes, compare the amplitude and timing, as well as spatial distribution of the ERP response after attended stimuli, against those during the passive condition.</li>
	<li>To identify the time course of ignoring, compare the amplitude and timing, as well as spatial distribution of the ERP response after ignored stimuli, against those during the passive condition.</li>
</ol>

<ol>
	<li>Desimone, R., Duncan, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Neural+Mechanisms+of+Selective+Visual-Attention.">Neural Mechanisms of Selective Visual-Attention.</a> Annu. Rev. Neurosci. 18, 193-222 (1995).</li><li>Hillyard, S. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Electrophysiology+of+Human+Selective+Attention.">Electrophysiology of Human Selective Attention.</a> Trends Neurosci. 8, 400-405 (1985).</li><li>Kastner, S., Ungerleider, L. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+neural+basis+of+biased+competition+in+human+visual+cortex.">The neural basis of biased competition in human visual cortex.</a> Neuropsychologia. 39, 1263-1276 (2001).</li><li>Mangun, G. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Neural+Mechanisms+of+Visual+Selective+Attention.">Neural Mechanisms of Visual Selective Attention.</a> Psychophysiology. 32, 4-18 (1995).</li><li>Chadick, J. Z., Gazzaley, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Differential+coupling+of+visual+cortex+with+default+or+frontal-parietal+network+based+on+goals.">Differential coupling of visual cortex with default or frontal-parietal network based on goals.</a> Nat Neurosci. 14, 830-832 (2011).</li><li>Ruff, C. C., Driver, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Attentional+preparation+for+a+lateralized+visual+distractor:+behavioral+and+fMRI+evidence.">Attentional preparation for a lateralized visual distractor: behavioral and fMRI evidence.</a> J Cogn Neurosci. 18, 522-538 (2006).</li><li>Serences, J. T., Yantis, S., Culberson, A., Awh, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Preparatory+activity+in+visual+cortex+indexes+distractor+suppression+during+covert+spatial+orienting.">Preparatory activity in visual cortex indexes distractor suppression during covert spatial orienting.</a> J Neurophysiol. 92, 3538-3545 (2004).</li><li>Rissman, J., Gazzaley, A., D'Esposito, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+effect+of+non-visual+working+memory+load+on+top-down+modulation+of+visual+processing.">The effect of non-visual working memory load on top-down modulation of visual processing.</a> Neuropsychologia. 47, 1637-1646 (2009).</li><li>Gazzaley, A., Cooney, J. W., Rissman, J., D'Esposito, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Top-down+suppression+deficit+underlies+working+memory+impairment+in+normal+aging.">Top-down suppression deficit underlies working memory impairment in normal aging.</a> Nat Neurosci. 8, 1298-1300 (2005).</li><li>Kong, D. Y., Soon, C. S., Chee, M. W. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Functional+imaging+correlates+of+impaired+distractor+suppression+following+sleep+deprivation.">Functional imaging correlates of impaired distractor suppression following sleep deprivation.</a> NeuroImage. 61, 50-55 (2012).</li><li>Luck, S. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effects+of+Spatial+Cueing+on+Luminance+Detectability+-+Psychophysical+and+Electrophysiological+Evidence+for+Early+Selection.">Effects of Spatial Cueing on Luminance Detectability - Psychophysical and Electrophysiological Evidence for Early Selection.</a> J Exp Psychol Human. 20, 887-904 (1994).</li><li>Posner, M. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Orienting+of+Attention.">Orienting of Attention.</a> QJ Exp Psychol. 32, 3-25 (1980).</li><li>Posner, M. I., Nissen, M. K., Ogden, W. C., Pick, H., Saltzmann, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Modes of Perceiving and Processing Information. , 137-157 (1978).</li><li>Gazzaley, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Influence+of+early+attentional+modulation+on+working+memory.">Influence of early attentional modulation on working memory.</a> Neuropsychologia. 49, 1410-1424 (2011).</li><li>Johnson, J. A., Zatorre, R. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Attention+to+simultaneous+unrelated+auditory+and+visual+events:+Behavioral+and+neural+correlates.">Attention to simultaneous unrelated auditory and visual events: Behavioral and neural correlates.</a> Cereb Cortex. 15, 1609-1620 (2005).</li><li>Johnson, J. A., Zatorre, R. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Neural+substrates+for+dividing+and+focusing+attention+between+simultaneous+auditory+and+visual+events.">Neural substrates for dividing and focusing attention between simultaneous auditory and visual events.</a> NeuroImage. 31, 1673-1681 (2006).</li><li>Zanto, T. P., Gazzaley, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Neural+Suppression+of+Irrelevant+Information+Underlies+Optimal+Working+Memory+Performance.">Neural Suppression of Irrelevant Information Underlies Optimal Working Memory Performance.</a> J Neurosci. 29, 3059-3066 (2009).</li><li>Lenartowicz, A., Simpson, G. V., Haber, C. M., Cohen, M. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Neurophysiological+Signals+of+Ignoring+and+Attending+Are+Separable+and+Related+to+Performance+during+Sustained+Intersensory+Attention.">Neurophysiological Signals of Ignoring and Attending Are Separable and Related to Performance during Sustained Intersensory Attention.</a> J Cogn Neurosci. , 1-15 (2014).</li><li>Daffner, K. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Does+modulation+of+selective+attention+to+features+reflect+enhancement+or+suppression+of+neural+activity.">Does modulation of selective attention to features reflect enhancement or suppression of neural activity.</a> Biol Psychol. 89, 398-407 (2012).</li><li>Weissman, D. H., Warner, L. M., Woldorff, M. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Momentary+reductions+of+attention+permit+greater+processing+of+irrelevant+stimuli.">Momentary reductions of attention permit greater processing of irrelevant stimuli.</a> NeuroImage. 48, 609-615 (2009).</li><li>Shams, L., Kamitani, Y., Shimojo, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Visual+illusion+induced+by+sound.">Visual illusion induced by sound.</a> Cognitive Brain Res. 14, 147-152 (2002).</li><li>Di Luca, M., Machulla, T. K., Ernst, M. O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Recalibration+of+multisensory+simultaneity:+Cross-modal+transfer+coincides+with+a+change+in+perceptual+latency.">Recalibration of multisensory simultaneity: Cross-modal transfer coincides with a change in perceptual latency.</a> J Vision. 9, (2009).</li><li>Makeig, S., Jung, T. P., Bell, A. J., Ghahremani, D., Sejnowski, T. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Blind+separation+of+event-related+brain+response+components.">Blind separation of event-related brain response components.</a> Psychophysiology. 33, S58-S58 (1996).</li><li>Baillet, S., Mosher, J. C., Leahy, R. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Electromagnetic+brain+mapping.">Electromagnetic brain mapping.</a> IEEE Signal Processing Mag. 18, 14-30 (2001).</li><li>Garcia-Perez, M. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Forced-choice+staircases+with+fixed+step+sizes+asymptotic+and+small-sample+properties.">Forced-choice staircases with fixed step sizes asymptotic and small-sample properties.</a> Vision Res. 38, 1861-1881 (1998).</li><li>Picton, T. W., Bentin, S., Berg, P., Donchin, E., Hilllyard, S. A., Johnson, R. J. R., Miller, G. A., Ritter, W., Ruchkin, D. S., Rugg, M. D., Taylor, M. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Guidelines+for+using+human+event-related+potentials+to+study+cognition:+Recroding+standards+and+publication+criteria.">Guidelines for using human event-related potentials to study cognition: Recroding standards and publication criteria.</a> Psychophysiology. 37 (2), 127-152 (2000).</li><li>Keil, A., Debener, S., Gratton, G., Junghofer, M., Kappenman, E. S., Luck, S. J., Luu, P., Miller, G. A., Yee, C. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Committee+Report:+Publication+guidelines+and+recommendations+for+studies+using+electroencephalography+and+magnetoencephalography.">Committee Report: Publication guidelines and recommendations for studies using electroencephalography and magnetoencephalography.</a> Psychophysiology. 51 (1), 1-21 (2014).</li></ol>

The authors have nothing to disclose.

Processes related to attending and to ignoring in attention control may involve different neural pathways and time courses. Therefore, it is of value to measure these processes separately. The IMAT is a tool, by which one may capture neurophysiological signals of attending and ignoring separately, but concurrently, in sustained attention. The critical steps include the measurement of sensory neurophysiological responses when the participant is attending, ignoring or passively perceiving stimuli presented in a given modal...

Attention control guides behavior by directing our neural and cognitive resources toward select input signals, while restricting access to other signals, based on a given behavioral goal 1. For instance, when reading a book, the visual signals corresponding to the book are the target signals to be enhanced, whereas other sensory signals &#8212; such as the TV in the next room &#8212; are distractor signals to be attenuated. Recordings in both human and non-human primates 1-4, indicate that neural responses in sensory cortices are enhanced for attended targets relative to ignored distractors during selective attention, indicating that the strength of sensory inputs in the brain is modulated as a function of whether they are classified as targets or distractors 5-7. We refer to this difference in signal strength when attending versus ignoring as the attention modulation effect.
Of increasing interest is the question of whether and how the neural processes of attending contribute to attention control and its impairments, separately from the neural processes of ignoring. It is increasingly clear that the ability to ignore distractions can be impaired independently from our ability to attend targets. For instance, distractor-suppression can be impaired with increased task load 8, cognitive aging 9 and sleep deprivation 10, without a decrement in target enhancement. It is not currently known if a decrement in target enhancement can also exist without a deficit in distractor suppression. Perhaps more importantly, it is not resolved whether deficits of either attending or ignoring, but not both, can elucidate neuropsychiatric conditions in which attention control is impaired. As such, it is valuable to better understand whether attending and ignoring arise from separable cortical pathways, if and how they differ in neural dynamics. By measuring attending and ignoring processes separately, such questions can be addressed.
Here we describe methodology to measure the neurophysiological signals of attending and ignoring separately, but concurrently, in sustained attention. This approach builds on the attention modulation effect: the difference in amplitude of a neural sensory response when the individual is attending versus ignoring to stimuli in that sensory stream. The attention modulation effect is a powerful tool for detecting attention modulation over sensory signals, but it precludes the ability to assess the separate dynamics of attending and ignoring processes. Namely, a difference in neural sensory responses when attending versus ignoring could arise because the process of attention enhances sensory target signals, or because ignoring attenuates sensory distractor signals, or both. To test between these alternatives, the use of an additional control condition is required in which one quantifies the strength of sensory inputs at their natural baseline, when they are neither attended nor ignored. This is similar to walking down a busy street full of cars, but neither actively watching (e.g., for a taxi) nor actively ignoring (e.g., non-taxi cars and buses) the passing cars. By evaluating sensory signals that are attended or ignored, relative to a passive reference condition, the magnitude and timing of attending and ignoring processes can be quantified separately.
Effective uses of such a passive control in measuring attending and ignoring processes have been reported previously in studies of anticipatory attention 11-13 and memory-attention interactions 9,10,14-17. Here we describe the use of this approach in the context of sustained attention, in a non-cued, continuous, intermodal (i.e., auditory-visual) attention task (IMAT) 18. In other words, this method is appropriate to the study of ongoing rather than preparatory control processes, allowing for tracking of these processes across time. This method also quantifies control processes that modulate sensory responses across different sensory modalities (i.e., auditory versus visual), thus focusing on processes that are not specialized to within a particular sensory or content domain. Unlike previous functional magnetic resonance imaging studies 15,19,20, this method tracks attending and ignoring processes using temporally resolved neurophysiological signals (electroencephalography, EEG), thus providing millisecond resolution on the temporal profiles of attending and ignoring processes. Our representative results demonstrate the use of the technique in identifying direct evidence for separable cortical sources and temporal dynamics of the neural processes of attending and ignoring, and unique contributions to the attention modulation effect.

<table border="0" cellpadding="0" cellspacing="0">
	<tbody>
		<tr>
			<td>NetStation Software</td>
			<td>Electrical Geodesic, Inc.</td>
			<td>version 4.5.1</td>
			<td>Alternate recording software may be used.</td>
		</tr>
		<tr>
			<td>Matlab Software</td>
			<td>The MathWorks, Inc.</td>
			<td>7.10.0 (R2010a)</td>
			<td>Alternate analysis and presentation software may be used.</td>
		</tr>
		<tr>
			<td>PsychToolbox Software</td>
			<td>http://psychtoolbox.org/</td>
			<td>v3.0.8 (2010-03-06)</td>
			<td>Open-source software. Alternate stimulus presentation software may be used.</td>
		</tr>
		<tr>
			<td>Netstation Amplifier</td>
			<td>Electrical Geodesic, Inc.</td>
			<td>300</td>
			<td>Alternate amplifier may be used.</td>
		</tr>
		<tr>
			<td>EEG Net</td>
			<td>Electrical Geodesic, Inc.</td>
			<td>HCGSN130</td>
			<td>Alternate EEG cap may be used.</td>
		</tr>
		<tr>
			<td>Saline-Based Electrolyte (Potassium Chloride)</td>
			<td>Electrical Geodesic, Inc.</td>
			<td>n/a</td>
			<td>Electrolyte used in soaking of net for this high-impedance EEG system. Alternate electrolyte mediate can be used.</td>
		</tr>
	</tbody>
</table>

measurement of neurophysiological signals of ignoring and attending processes in attention control

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

The IMAT protocol has been used previously to identify the unique contributions of attending and ignoring processes to response speed during sustained attention 18. In that study, we tested 35 healthy right-handed individuals (22 female, age: x&#773; = 21.0, &#963; = 5.4), recruited through the Psychology department subject pool at the University of California, Los Angeles. All participants provided written informed consent prior to participating in the study. Representative results highlight the value of meas...

Watch this Scientific Journal Video about Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control at JoVE.com

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

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

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

measurement-neurophysiological-signals-ignoring-attending-processes

Microsoft Bing

Research

JoVE Journal

Behavior

9.0K Views.  University of California Los Angeles. Attention control comprises enhancement of target signals and attenuation of distractor signals. We describe an approach to measure separately but concurrently, the neurophysiology of attending and ignoring in sustained intermodal attention, utilizing a passive control condition during which neither process is continuously engaged. 

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

Methods to Explore the Influence of Top-down Visual Processes on Motor Behavior

Kinesthetic awareness is important to successfully navigate the environment. When we interact with our daily surroundings, some aspects of movement are deliberately planned, while others spontaneously occur below conscious awareness. The deliberate component of this dichotomy has been studied extensively in several contexts, while the spontaneous component remains largely under-explored. Moreover, how perceptual processes modulate these movement classes is still unclear. In particular, a currently debated issue is whether the visuomotor system is governed by the spatial percept produced by a visual illusion or whether it is not affected by the illusion and is governed instead by the veridical percept. Bistable percepts such as 3D depth inversion illusions (DIIs) provide an excellent context to study such interactions and balance, particularly when used in combination with reach-to-grasp movements. In this study, a methodology is developed that uses a DII to clarify the role of top-down processes on motor action, particularly exploring how reaches toward a target on a DII are affected in both deliberate and spontaneous movement domains.

It is unclear how top-down signals from the ventral visual stream affect movement. We developed a paradigm to test motor behavior towards a target on a 3D depth inversion illusion. Significant differences are reported in both deliberate, goal-directed movements and automatic actions under illusory and veridical viewing conditions.

Kinesthetic awareness is important to successfully navigate the environment. When we interact with our daily surroundings, some aspects of movement are ...

The 5-Choice Serial Reaction Time Task: A Task of Attention and Impulse Control for Rodents

This protocol describes the 5-choice serial reaction time task, which is an operant based task used to study attention and impulse control in rodents. Test day challenges, modifications to the standard task, can be used to systematically tax the neural systems controlling either attention or impulse control. Importantly, these challenges have consistent effects on behavior across laboratories in intact animals and can reveal either enhancements or deficits in cognitive function that are not apparent when rats are only tested on the standard task. The variety of behavioral measures that are collected can be used to determine if other factors (i.e., sedation, motivation deficits, locomotor impairments) are contributing to changes in performance. The versatility of the 5CSRTT is further enhanced because it is amenable to combination with pharmacological, molecular, and genetic techniques.

This protocol describes the 5-choice serial reaction time task, which is an operant based task used to study attention and impulse control in rodents. Test day challenges, which are modifications of the standard task, increase flexibility of the task and can be combined with other manipulations to more fully characterize behavior.

This protocol describes the 5-choice serial reaction time task, which is an operant based task used to study attention and impulse control in rodents. ...

Methods to Test Visual Attention Online

Online data collection methods have particular appeal to behavioral scientists because they offer the promise of much larger and much more representative data samples than can typically be collected on college campuses. However, before such methods can be widely adopted, a number of technological challenges must be overcome &#8211; in particular in experiments where tight control over stimulus properties is necessary. Here we present methods for collecting performance data on two tests of visual attention. Both tests require control over the visual angle of the stimuli (which in turn requires knowledge of the viewing distance, monitor size, screen resolution, etc.) and the timing of the stimuli (as the tests involve either briefly flashed stimuli or stimuli that move at specific rates). Data collected on these tests from over 1,700 online participants were consistent with data collected in laboratory-based versions of the exact same tests. These results suggest that with proper care, timing/stimulus size dependent tasks can be deployed in web-based settings.

To replicate laboratory settings, online data collection methods for visual tasks require tight control over stimulus presentation. We outline methods for the use of a web application to collect performance data on two tests of visual attention.

Online data collection methods have particular appeal to behavioral scientists because they offer the promise of much larger and much more representative ...

Assessing the Multiple Dimensions of Engagement to Characterize Learning: A Neurophysiological Perspective

In a recent theoretical synthesis on the concept of engagement, Fredricks, Blumenfeld and Paris1 defined engagement by its multiple dimensions: behavioral, emotional and cognitive. They observed that individual types of engagement had not been studied in conjunction, and little information was available about interactions or synergy between the dimensions; consequently, more studies would contribute to creating finely tuned teaching interventions. Benefiting from the recent technological advances in neurosciences, this paper presents a recently developed methodology to gather and synchronize data on multidimensional engagement during learning tasks. The technique involves the collection of (a) electroencephalography, (b) electrodermal, (c) eye-tracking, and (d) facial emotion recognition data on four different computers. This led to synchronization issues for data collected from multiple sources. Post synchronization in specialized integration software gives researchers a better understanding of the dynamics between the multiple dimensions of engagement. For curriculum developers, these data could provide informed guidelines for achieving better instruction/learning efficiency. This technique also opens up possibilities in the field of brain-computer interactions, where adaptive learning or assessment environments could be developed.

This paper aims to describe the techniques involved in the collection and synchronization of the multiple dimensions (behavioral, affective and cognitive) of learners&#8217; engagement during a task.

In a recent theoretical synthesis on the concept of engagement, Fredricks, Blumenfeld and Paris1 defined engagement by its multiple dimensions: ...

Force and Position Control in Humans - The Role of Augmented Feedback

During motor behaviour, humans interact with the environment by for example manipulating objects and this is only possible because sensory feedback is constantly integrated into the central nervous system and these sensory inputs need to be weighted in order meet the task specific goals. Additional feedback presented as augmented feedback was shown to have an impact on motor control and motor learning. A number of studies investigated whether force or position feedback has an influence on motor control and neural activation. However, as in the previous studies the presentation of the force and position feedback was always identical, a recent study assessed whether not only the content but also the interpretation of the feedback has an influence on the time to fatigue of a sustained submaximal contraction and the (inhibitory) activity of the primary motor cortex using subthreshold transcranial magnetic stimulation. This paper describes one possible way to investigate the influence of the interpretation of feedback on motor behaviour by investigating the time to fatigue of submaximal sustained contractions together with the neuromuscular adaptations that can be investigated using surface EMG. Furthermore, the current protocol also describes how motor cortical (inhibitory) activity can be investigated using subthreshold TMS, a method known to act solely on the cortical level. The results show that when participants interpret the feedback as position feedback, they display a significantly shorter time to fatigue of a submaximal sustained contraction. Furthermore, subjects also displayed an increased inhibitory activity of the primary cortex when they believed to receive position feedback compared when they believed to receive force feedback. Accordingly, the results show that interpretation of feedback results in differences on a behavioural level (time to fatigue) that is also reflected in interpretation-specific differences in the amount of inhibitory M1 activity.

Controlling an identical movement with position or force feedback results in different neural activation and motor behavior. This protocol describes how to investigate behavioral changes by looking at neuromuscular fatigue and how to evaluate motor cortical (inhibitory) activity using subthreshold TMS with respect to the interpretation of augmented feedback.

During motor behaviour, humans interact with the environment by for example manipulating objects and this is only possible because sensory feedback is ...

Combined Invasive Subcortical and Non-invasive Surface Neurophysiological Recordings for the Assessment of Cognitive and Emotional Functions in Humans

In spite of the success in applying non-invasive electroencephalography (EEG), magneto-encephalography (MEG) and functional magnetic resonance imaging (fMRI) for extracting crucial information about the mechanism of the human brain, such methods remain insufficient to provide information about physiological processes reflecting cognitive and emotional functions at the subcortical level. In this respect, modern invasive clinical approaches in humans, such as deep brain stimulation (DBS), offer a tremendous possibility to record subcortical brain activity, namely local field potentials (LFPs) representing coherent activity of neural assemblies from localized basal ganglia or thalamic regions. Notwithstanding the fact that invasive approaches in humans are applied only after medical indication and thus recorded data correspond to altered brain circuits, valuable insight can be gained regarding the presence of intact brain functions in relation to brain oscillatory activity and the pathophysiology of disorders in response to experimental cognitive paradigms. In this direction, a growing number of DBS studies in patients with Parkinson&#39;s disease (PD) target not only motor functions but also higher level processes such as emotions, decision-making, attention, memory and sensory perception. Recent clinical trials also emphasize the role of DBS as an alternative treatment in neuropsychiatric disorders ranging from obsessive compulsive disorder (OCD) to chronic disorders of consciousness (DOC). Consequently, we focus on the use of combined invasive (LFP) and non-invasive (EEG) human brain recordings in assessing the role of cortical-subcortical structures in cognitive and emotional processing trough experimental paradigms (e.g. speech stimuli with emotional connotation or paradigms of cognitive control such as the Flanker task), for patients undergoing DBS treatment.

The present protocol aims at assessing cognitive-emotional functions in the basal ganglia by simultaneous neurophysiological recording of local field potentials and non-invasive brain cortical activity (EEG). The procedure is exemplified by the use of paradigms involving speech stimuli with emotional connotation or the Flanker task involving cognitive control.

In spite of the success in applying non-invasive electroencephalography (EEG), magneto-encephalography (MEG) and functional magnetic resonance imaging ...

Investigating Motor Skill Learning Processes with a Robotic Manipulandum

Skilled reaching tasks are commonly used in studies of motor skill learning and motor function under healthy and pathological conditions, but can be time-intensive and ambiguous to quantify beyond simple success rates. Here, we describe the training procedure for reach-and-pull tasks with ETH Pattus, a robotic platform for automated forelimb reaching training that records pulling and hand rotation movements in rats. Kinematic quantification of the performed pulling attempts reveals the presence of distinct temporal profiles of movement parameters such as pulling velocity, spatial variability of the pulling trajectory, deviation from midline, as well as pulling success. We show how minor adjustments in the training paradigm result in alterations in these parameters, revealing their relation to task difficulty, general motor function or skilled task execution. Combined with electrophysiological, pharmacological and optogenetic techniques, this paradigm can be used to explore the mechanisms underlying motor learning and memory formation, as well as loss and recovery of function (e.g. after stroke).

A paradigm is presented for training and analysis of an automated skilled reaching task in rats. Analysis of pulling attempts reveals distinct subprocesses of motor learning.

Skilled reaching tasks are commonly used in studies of motor skill learning and motor function under healthy and pathological conditions, but can be ...

Central and Divided Visual Field Presentation of Emotional Images to Measure Hemispheric Differences in Motivated Attention

Two dominant theories on lateralized processing of emotional information exist in the literature. One theory posits that unpleasant emotions are processed by right frontal regions, while pleasant emotions are processed by left frontal regions. The other theory posits that the right hemisphere is more specialized for the processing of emotional information overall, particularly in posterior regions.
Assessing the different roles of the cerebral hemispheres in processing emotional information can be difficult without the use of neuroimaging methodologies, which are not accessible or affordable to all scientists. Divided visual field presentation of stimuli can allow for the investigation of lateralized processing of information without the use of neuroimaging technology. 
This study compared central versus divided visual field presentations of emotional images to assess differences in motivated attention between the two hemispheres. The late positive potential (LPP) was recorded using electroencephalography (EEG) and event-related potentials (ERPs) methodologies to assess motivated attention. Future work will pair this paradigm with a more active behavioral task to explore the behavioral impacts on the attentional differences found.

This study compared central versus divided visual field presentations of emotional images to assess differences in motivated attention between the two hemispheres. The late positive potential (LPP) was recorded using electroencephalography (EEG) and event-related potentials (ERPs) methodologies to assess motivated attention.

Two dominant theories on lateralized processing of emotional information exist in the literature. One theory posits that unpleasant emotions are processed ...

Gaze in Action: Head-mounted Eye Tracking of Children's Dynamic Visual Attention During Naturalistic Behavior

Young children's visual environments are dynamic, changing moment-by-moment as children physically and visually explore spaces and objects and interact with people around them. Head-mounted eye tracking offers a unique opportunity to capture children's dynamic egocentric views and how they allocate visual attention within those views. This protocol provides guiding principles and practical recommendations for researchers using head-mounted eye trackers in both laboratory and more naturalistic settings. Head-mounted eye tracking complements other experimental methods by enhancing opportunities for data collection in more ecologically valid contexts through increased portability and freedom of head and body movements compared to screen-based eye tracking. This protocol can also be integrated with other technologies, such as motion tracking and heart-rate monitoring, to provide a high-density multimodal dataset for examining natural behavior, learning, and development than previously possible. This paper illustrates the types of data generated from head-mounted eye tracking in a study designed to investigate visual attention in one natural context for toddlers: free-flowing toy play with a parent. Successful use of this protocol will allow researchers to collect data that can be used to answer questions not only about visual attention, but also about a broad range of other perceptual, cognitive, and social skills and their development.

Gaze in Action: Head-mounted Eye Tracking of Children&#039;s Dynamic Visual Attention During Naturalistic Behavior

Young children do not passively observe the world, but rather actively explore and engage with their environment. This protocol provides guiding principles and practical recommendations for using head-mounted eye trackers to record infants' and toddlers' dynamic visual environments and visual attention in the context of natural behavior.

Young children's visual environments are dynamic, changing moment-by-moment as children physically and visually explore spaces and objects and interact ...

Measurement of Spatial Stability in Precision Grip

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

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