Concurrent Assessment of Sequential Auditory Event-related Potentials Using an Optimized Paired-stimulus Local-global Paradigm

Concurrent Assessment of Sequential Auditory Event-related Potentials Using an Optimized Paired-stimulus Local-global Paradigm | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL European Journal of Neuroscience This is a preprint and has not been peer reviewed. Data may be preliminary. 3 October 2025 V1 Latest version Share on Concurrent Assessment of Sequential Auditory Event-related Potentials Using an Optimized Paired-stimulus Local-global Paradigm Authors : Chao Guo 0009-0003-2946-620X , Xiaoyu Wang 0000-0002-0828-6328 [email protected] , Zhaonan Ma 0009-0007-8453-5916 , Xiao Yang , and Fengyu Cong Authors Info & Affiliations https://doi.org/10.22541/au.175952328.82883388/v1 Published European Journal of Neuroscience Version of record Peer review timeline 222 views 152 downloads Contents Abstract 2.4.1 Group-level characteristics analysis 2.4.2 Individual-level sensitivity analysis 2.4.3 Active-passive classification across varying EEG configurations Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Comprehensive assessment of auditory processing is crucial for understanding perceptual and attentional functions, as well as detecting related deficits in clinical populations. Auditory event-related potentials (ERPs) track key stages through time-locked components that emerge from early sensory processing (P1-N1-P2 complex) and automatic deviance detection (mismatch negativity, MMN) to involuntary attention orienting (P3a) and voluntary attention engagement (P3b). However, current approaches predominantly focus on isolated ERP components demonstrated through group-level statistical difference, while paradigms capable of capturing sequential components with high individual sensitivity remain scarce. Here, we optimized the local-global paradigm with paired-stimulus design, strategically capturing pre-attentive to voluntary processing by contrasting responses to within-pair violations (local effect) versus across-pair violations (global effect). We evaluated this paradigm in 30 healthy participants under active (target counting) and passive (visual distraction) conditions. Results demonstrated that both conditions reliably elicited complete pre-attentive components (P1-N1-P2 and MMN) as confirmed by cluster-based permutation tests, achieving 30/30 individual-level sensitivity validated through intrasubject classification analysis. Furthermore, comparison between active and passive conditions revealed significant differences specifically in the 272-392ms and 272-400ms window (p < 0.05) under two levels of global deviants. This contrast successfully dissociated voluntary from involuntary attention with 86.67% and 93.33% individual sensitivity, respectively. Moreover, the active-passive discrimination depended primarily on the number of epochs sampled (p0.05). These findings validate our paired-stimulus local-global paradigm as a reliable approach for assessing sequential auditory ERPs, offering significant advantages with potential applications in clinical evaluation of perceptual and attentional impairments. Title: Concurrent Assessment of Sequential Auditory Event-related Potentials Using an Optimized Paired-stimulus Local-global Paradigm Chao Guo 1 | Xiaoyu Wang 2,3 | Zhaonan Ma 1 ,4 | Xiao Yang 1 | Fengyu Cong 1,4,5 1 School of Biomedical Engineering, Faculty of Medicine, Dalian University of Technology, Dalian 116024, China 2 Western Institute of Neuroscience, Western University, London ON N6A 5B7, Canada 3 Department of Physiology and Pharmacology, Western University, London, Canada. 4 Faculty of Information Technology, University of Jyväskylä, FI-40014 Jyväskylä, Finland 5 Key Laboratory of Social Computing and Cognitive Intelligence (Dalian University of Technology), Ministry of Education, China Correspondence: Xiaoyu Wang, Western Institute of Neuroscience, Western University, London, Canada. Department of Physiology and Pharmacology, Western University, London, Canada. E-mail: [email protected] Data and code availability statement: The code for the paired-stimulus local-global paradigm, the code for data analysis, and the processed data are available at https://github.com/GuoChao1250. Raw EEG data is available upon request. Conflict of interest disclosure: The authors declare no competing interests. Author contribution statement: Chao Guo and Xiaoyu Wang contributed equally. Chao Guo: methodology, investigation, experiment, data curation and analysis, visualization, writing-original draft, writing-review & editing; Xiaoyu Wang: conceptualization, methodology, supervision, writing-review & editing; Zhaonan Ma: methodology, writing-review; Xiao Yang: investigation, data analysis; Fengyu Cong: conceptualization, methodology, supervision, writing-review. Funding statement: Science and Technology Planning Project of Liaoning Province (no. 2021JH1/10400049) Liaoning Provincial Key Laboratory of Intelligent construction IoT Application Technology, 2024KFKT-08 Ethics approval statement: The study was approved by the Ethics Committee of Dalian University of Technology (DUTFM250630-01). Concurrent Assessment of Sequential Auditory Event-related Potentials Using an Optimized Paired-stimulus Local-global Paradigm Abstract : Comprehensive assessment of auditory processing is crucial for understanding perceptual and attentional functions, as well as detecting related deficits in clinical populations. Auditory event-related potentials (ERPs) track key stages through time-locked components that emerge from early sensory processing (P1-N1-P2 complex) and automatic deviance detection (mismatch negativity, MMN) to involuntary attention orienting (P3a) and voluntary attention engagement (P3b). However, current approaches predominantly focus on isolated ERP components demonstrated through group-level statistical difference, while paradigms capable of capturing sequential components with high individual sensitivity remain scarce. Here, we optimized the local-global paradigm with paired-stimulus design, strategically capturing pre-attentive to voluntary processing by contrasting responses to within-pair violations (local effect) versus across-pair violations (global effect). We evaluated this paradigm in 30 healthy participants under active (target counting) and passive (visual distraction) conditions. Results demonstrated that both conditions reliably elicited complete pre-attentive components (P1-N1-P2 and MMN) as confirmed by cluster-based permutation tests, achieving 30/30 individual-level sensitivity validated through intrasubject classification analysis. Furthermore, comparison between active and passive conditions revealed significant differences specifically in the 272-392ms and 272-400ms window (p < 0.05) under two levels of global deviants. This contrast successfully dissociated voluntary from involuntary attention with 86.67% and 93.33% individual sensitivity, respectively. Moreover, the active-passive discrimination depended primarily on the number of epochs sampled (p 0.05). These findings validate our paired-stimulus local-global paradigm as a reliable approach for assessing sequential auditory ERPs, offering significant advantages with potential applications in clinical evaluation of perceptual and attentional impairments. Key words: Event-related Potentials (ERPs), Mismatch Negativity (MMN), Voluntary Attention, Local-global, P3b 1. Introduction Auditory processing unfolds through sequential stages, from early sensory encoding and automatic deviance detection to involuntary attention orienting and voluntary attention engagement, providing a framework for evaluating perceptual and attentional functions (Nelken et al., 2014; Peterson et al., 2025; Price & Moncrieff, 2021). The integrity of this hierarchical processing is crucial, as disruptions at any stage can degrade diagnostic sensitivity through cascading propagation of neural deficits. Specifically, compromised sensory gating precludes reliable deviance detection, while impaired automatic processing obscures conscious attention allocation (Comanducci et al., 2020; Sergent et al., 2021). Consequently, precise localization of impairment along the auditory processing pathway becomes essential for reliable neurocognitive assessment. This need is particularly important in disorders of consciousness (DOC), where behavioral responses are absent or ambiguous, yet preserved auditory processing may indicate covert consciousness undetectable through clinical examination (Sitt et al., 2014). Objective neurophysiological measurements thus provide a valuable window into these patients’ cognitive capacities. Auditory event-related potentials (ERPs) offer millisecond-precision tracking of sequential neural processes through distinct time-locked components. Early components reflect automatic and pre-attentive processing that occurs without conscious awareness. The P1-N1-P2 complex (50-200ms) emerges as an obligatory response to any auditory stimulus, representing basic sensory registration (Näätänen & Picton, 1987). In contrast, mismatch negativity (MMN, 100-250ms) is specifically elicited when infrequent deviant sounds violate the regularity established by repetitive standards, indexing automatic change detection (Garrido et al., 2009; Näätänen et al., 2007). These components can be reliably recorded during passive listening, when participants’ attention is directed elsewhere through reading or visual tasks, and persist even in unresponsive patients with preserved sensory function. This independence from conscious attention confirms their automatic nature and establishes their value as objective markers of intact early auditory processing (Fischer et al., 2010; Näätänen et al., 2012). Following these pre-attentive components, later ERPs reveal how attention modulates auditory processing. The P3a component (250-350ms) reflects involuntary attention orienting, emerging when salient or unexpected stimuli automatically capture attention regardless of task demands (Atienza et al., 2001). This frontocentral response occurs even during passive conditions, distinguishing it from the P3b component (300-500ms), which manifests exclusively during active target detection tasks (Rutiku et al., 2024). Unlike P3a’s automatic emergence, P3b requires voluntary attention allocation and reflects conscious stimulus evaluation, appearing over centroparietal regions (Barry et al., 2016; Polich, 2007). This functional dissociation between P3a and P3b, demonstrable by comparing active counting tasks with passive listening conditions, provides crucial insights into attentional hierarchies. In clinical populations, particularly in patients with DOC, preserved P3a with absent P3b indicates intact bottom-up attention orienting despite impaired conscious integration functions (Kotchoubey et al., 2005; Sergent et al., 2005). Therefore, paradigms capable of reliably eliciting and dissociating these attention-related components at the individual level are essential for accurate assessment of residual cognitive function. These sequential components, from pre-attentive to voluntary processing, collectively offer a comprehensive view of auditory cognitive function. However, current paradigms face significant limitations in harnessing this diagnostic potential for clinical assessment. Most approaches require separate experimental sessions to evaluate different components, creating a fragmented assessment approach. Specifically, these include passive oddball for pre-attentive responses (P1-N1-P2 and MMN), novelty paradigms using salient stimuli like the subject’s own name for P3a, and active target tasks for P3b (Barry et al., 2016; Garrido et al., 2009; Merchie & Gomot, 2023; Morlet et al., 2017; Sculthorpe-Petley et al., 2015). This fragmentation proves particularly problematic in DOC patients, whose fluctuating arousal states make multiple testing sessions unreliable or impossible (Edlow et al., 2021). The local-global paradigm partly addresses this fragmentation by embedding multiple regularity levels within a single auditory sequence. Local regularities (within-trial acoustic patterns) probe pre-attentive processing, while global regularities (across-trial sequence violations) engage higher-order conscious detection, enabling concurrent assessment of different processing stages (Bekinschtein et al., 2009; King et al., 2013). However, critical gaps remain for clinical translation. Current implementations focus narrowly on MMN and P3b, providing an incomplete picture of the sequential processing hierarchy. While these studies demonstrate robust group-level effects, few have systematically validated individual-level sensitivity essential for clinical diagnosis. To address these limitations, we developed an optimized paired-stimulus local-global paradigm designed to temporally separate local (within-pair deviations) and global (across-pair violations) effects under both active and passive conditions. Our primary goal was to validate its ability to reliably elicit the full sequence of auditory ERPs with high individual sensitivity in a single session and determine whether task-based contrasts can effectively separate P3a from P3b in individual recordings. Specifically, we hypothesized that: (1) robust early sensory (P1-N1-P2 complex), pre-attentive (MMN) and involuntary attention (P3a) components would be elicited across individuals regardless of tasks, (2) the active-passive contrast would selectively modulate the P3b, thereby dissociating voluntary from involuntary attentional processes, and (3) the reliable detection of the voluntary attention effect would be more critically dependent on temporal sampling (the number of trials) than spatial resolution (the number of sensors). Demonstrating this research provides essential groundwork for translating ERP-based consciousness assessment into clinical practice, particularly for intensive care patients with fluctuating arousal states. 2. Materials and methods 2.1. Participants 30 adult undergraduate participants (mean age 24.70 ± 1.37; 19 male) were recruited from Dalian University of Technology. All participants reported normal hearing, and none had a history of neurological or psychiatric illnesses. The study was approved by the Ethics Committee of Dalian University of Technology (DUTFM250630-01). All participants gave written informed after obtaining knowledge of this experiment. 2.2 Stimulation paradigm The study employed a paired-stimulus local-global paradigm as illustrated in Figure 1. Three types of stimuli were used: 1000Hz standard tones (S), 1500Hz frequency-deviant tones (F), and numerical-deviant stimuli (N), with each stimulus having a duration of 200ms. In terms of the paired-stimulus, the first stimulus in each pair was always S, resulting in three combinations with the following probability: S-S pairs (70.56%), S-F pairs (20.00%), and S-N pairs (9.44%). Within this paradigm, local deviants were defined as any pair where the second stimulus differed from the first, including Local SF (S-F pairs) and Local SN (S-N pairs). Global deviants were defined as violations of established patterns across sequences of pairs, including Global SS-SN (S-N pairs disrupting the global regularity established by repeated S-S pairs) and Global SF-SN (S-N pairs disrupting the global regularity established by repeated S-F pairs). The numerical pairs were interspersed pseudo-randomly throughout the sequence, with the constraint that any two S-N pairs were separated by at least three other pairs (either S-S or S-F). The stimulus onset asynchrony (SOA) between sounds within a stimulus pair was fixed at 350ms. Between pairs, a jittered interval ranging from 1000-1300 ms (with 50 ms steps) was implemented to enhance ERP signal quality by preventing anticipatory responses (Steven J Luck, 2014). The experiment comprised a total of 2730 pairs of stimuli, with the first 30 S-S pairs serving to establish regularity (excluded from analysis). Of the remaining 2700 pairs analyzed, there were 1905 S-S pairs, 540 S-F pairs (all functioning as Local SF ), and 255 S-N pairs (all serving as Local SN ). For the global effect analysis, these included 121 instances of Global SS-SN (S-N pairs disrupting S-S regularity) and 134 instances of Global SF-SN (S-N pairs disrupting S-F regularity). The experiment consisted of two sessions designed to contrast voluntary and involuntary attention processing. During both sessions, participants sat in a comfortable chair in a sound-attenuated booth and received instructions via text displayed on a computer screen. The auditory stimulation remained identical across both conditions, with stimuli delivered through dual-channel earphones. In the active attention condition, participants were instructed to mentally count the number of numerical target stimuli (S-N pairs) and report their total at the end of the session. In the passive attention condition, participants were instructed to focus on watching a silent movie (“Modern Times”) displayed on a laptop while ignoring the auditory stimuli (Figure 1, Bottom panels). Each session lasted approximately 40 minutes and was implemented using the Psychophysics Toolbox Version 3 (Brainard, 1997). Figure 1. Experimental design of the paired-stimulus local-global paradigm. Upper panels: Schematic illustration of the stimulation sequence. The paradigm consists of paired stimuli where the first sound in each pair is always a 1000Hz standard tone (S, blue), followed by either another 1000Hz standard tone (S, blue), a 1500Hz frequency-deviant tone (F, navy blue), or a numerical deviant stimulus (N, red). The stimulus onset asynchrony (SOA) between sounds within a pair was fixed at 350ms, while pairs were separated by a jittered interval ranging from 1000-1300ms. Local deviants were defined by acoustic changes within pairs (S-F and S-N), while global deviants were defined by pattern violations across sequences of pairs. Bottom panels: Illustration of the two attention conditions. In the active attention condition, participants were instructed to mentally count the numerical target stimuli (S-N pairs) while ignoring other stimuli. In the passive attention condition, participants watched a silent movie (“Modern Times”) while the identical auditory sequence was presented, allowing for comparison between voluntary and automatic processing of auditory regularities. 2.3. EEG recordings and Preprocessing EEG data were recorded with a 64-channel ANT recording device (ANT Neuro) configured by eego amplifier and Ag/AgCl electrodes according to the 10/20 International System. The sampling rate was 1000Hz and the electrode impedance of all subjects was kept below 20kΩ. Data were referenced online at the CPz electrode. The recorded data preprocessed using EEGLAB toolbox (Delorme & Makeig, 2004). Firstly, visual inspection was conducted to remove significant artifacts caused by body movements, amplifier clipping or bursts of EEG activity. Channels with excessive noise or poor signal quality were identified and spatially interpolated. Then, the inspected data underwent sequential filtering with a 50Hz notch filter, 1Hz high-pass filter and 30Hz low-pass filter in order. The filtered data were re-referenced offline to the mean potential of two mastoid sites and down-sampled to 250Hz. Artifacts of eye movement, muscle activity and electrode noise were identified and removed using independent component analysis (ICA) (Lee et al., 1999). 2.4 Data analysis The analysis followed a stepwise approach to evaluate both group-level ERP characteristics and individual-level sensitivity. We first examined whether this paradigm reliably elicited the target ERP components at the group level. We then quantified the individual-level sensitivity of each component using machine learning (ML) techniques. Finally, we compared active versus passive conditions to differentiate involuntary from voluntary attentive processing at both group and individual levels. 2.4.1 Group-level characteristics analysis We analyzed three aspects of brain responses to evaluate auditory ERP components. First, the obligatory P1-N1-P2 complex was examined by comparing the first standard stimulus (S) in each pair with the pre-stimulus resting state (RS). For S, we extracted a 450-ms epoch including a 100-ms pre-stimulus period, with baseline correction using the -100 to 0 ms window. For RS, we used the 450-ms interval immediately preceding S onset (-450 to 0 ms), with baseline correction using the -450 to -350 ms window. Standard S and RS trials with voltages exceeding ±100μV were concurrently rejected for the guarantee that the number of them was matched, resulting in 1331 ± 24 accepted trials per participant for S and RS, respectively. Subsequently, local effects were examined to identify MMN/P3a components by comparing deviant stimuli to standard stimuli within individual stimulus pairs. We analyzed two types of local effects: (1) Local SF effect, derived from S-F pairs by comparing the frequency deviant (F) to the preceding standard tone (S), and (2) Local SN effect, derived from S-N pairs by comparing the numerical deviant (N) to the preceding standard tone (S). We used the same epoch extraction and artifact rejection criteria as in the P1-N1-P2 analysis. After artifact rejection, we retained epochs including 530 ± 11 S-F trials per participant for Local SF analysis, and 250 ± 6 S-N trials per participant for Local SN analysis. Third, global effects were analyzed to disentangle P3a and P3b components by examining responses to global pattern violations across stimulus pairs. We assessed two types of global effects: (1) Global SS-SN effect, comparing the second stimulus in numerical deviant pairs (N) against the second stimulus in standard S-S pairs, and (2) Global SF-SN effect, comparing the second stimulus in numerical deviant pairs (N) against the second stimulus in frequency deviant (S-F) pairs. For global analyses, we extracted 900-ms epochs time-locked to the onset of the second stimulus in each pair, including a 100-ms pre-stimulus baseline period. Using the same artifact rejection criteria, we retained epochs including 118 ± 4 trials per participant for Global SS-SN analysis, and 130 ± 5 trials per participant for Global SF-SN analysis. At the group level, ERP components were characterized by cluster-based permutation approach with threshold-free cluster enhancement (TFCE). This analysis was performed on the individual-averaged waveforms, with paired t-tests conducted across participants. The empirical distribution was established through 1000 random permutations, with alpha level set at 0.05 (two-tailed). Significant clusters were identified when at least two neighboring electrodes showed significant effects at the same time point, with an additional requirement that effects persist for at least 20 ms to correct for multiple comparisons in the time domain. In the results section, we report the time range (onset/offset) of significant clusters and their corresponding statistical values at the representative electrodes (global effects were reported at Pz electrode, while other ERPs were reported at the Fz electrode). 2.4.2 Individual-level sensitivity analysis We implemented a ML approach to assess the individual-level sensitivity of each ERP component. The individual condition-comparison and epoch extraction method for three aspects of brain responses were similar to the group-level characteristics analysis. For P1-N1-P2 complex, two conditions were the first standard stimulus (S) in each pair and RS preceding S onset. For local effects, two conditions were standard and deviant stimuli within pairs. For global effects, two conditions were the second stimulus in numerical deviant pairs (N) and the second stimulus in pairs preceding S-N. Moreover, another comparison was between active and passive conditions under global effects. We focused on 0-300ms post-stimulus period for P1-N1-P2 complex and local effects, 0-400ms post-stimulus period for global effects. To enhance signal-to-noise ratio (SNR) while maintaining sufficient samples for classification, we reorganized the epoch data (trials × channels × time points). Each participant’s trials were divided into 50 non-overlapping blocks, with consecutive trials averaged within each block. For instance, 200 trials were grouped into 50 blocks of 4 trials each, yielding 50 averaged samples per condition. This resulted in balanced datasets of 100 samples (50 per condition) for binary classification. The classification pipeline employed support vector machine (SVM) approaches with default hyperparameters and 5-fold cross-validation to quantify component-specific discriminability of ERPs. Two distinct binary classification tasks were systematically conducted: (1) S and RS for P1-N1-P2 complex, (2) standards and deviants for local and global effects and (3) active and passive conditions for condition-comparison. Model performance was quantified using classification accuracy, computed as the mean proportion of correctly classified trials across all cross-validation folds. To establish significance, we implemented a permutation framework with 1000 iterations using true labels to generate the performance distribution, and 1000 iterations with randomly shuffled labels to create the null distribution. Components were considered reliably detected when classification accuracy exceeded the 95th percentile of the null distribution. 2.4.3 Active-passive classification across varying EEG configurations To establish whether voluntary attention detection could be achieved with reduced recording demands, we evaluated how classification performance changed when reducing either spatial coverage or temporal sampling. We tested 16 configurations in a 4×4 factorial design: sensors montages of 8, 16, 32, and 64 channels (selected to preserve 10-20 system topology) crossed with 25%, 50%, 75%, and 100% of available epochs. Each configuration underwent SVM classification using the pipeline described in Section 2.4.2, with active versus passive conditions serving as classification targets during global effect processing. Notably, since 25% of the available epochs are insufficient to provide 50 samples per condition, we used the original number of epochs as samples. To ensure robust performance estimates, we repeated 5-fold cross-validation 500 times per configuration. The relationship between classification accuracy and recording parameters was assessed using Spearman’s rank correlation, separately examining the effects of electrode count and epoch percentage. Statistical significance was determined through percentile bootstrap with 1000 iterations (Efron & Tibshirani, 1994), with 95% confidence intervals computed from the bootstrap distribution. 3. Results 3.1 Validation of component elicitation across conditions 3.1.1 P1-N1-P2 complex For the P1-N1-P2 complex, group-level comparison of standard stimuli with resting state at at Fz electrode revealed reliable component elicitation in both passive and active conditions (Figure 2.a, left panel). Three distinct clusters emerged with consistent temporal profiles: an positive P1 cluster (passive: 20-100 ms, p < 0.05, peak t = 124 at 76 ms; active: 24-100 ms, p < 0.05, peak t = 116 at 76 ms), followed by a negative N1 cluster (passive: 116-136 ms, p < 0.05, peak t = 34 at 124 ms; active: 116-144 ms, p < 0.05, peak t = 75 at 128 ms), and a positive P2 cluster (passive: 152-220 ms, p < 0.05, peak t = 300 at 184 ms; active: 160-228 ms, p < 0.05, peak t = 277 at 188 ms). At the individual level, the SVM classification between standard stimuli and resting state demonstrated exceptional detection sensitivity (Figure 2.b, left panel). All 30 participants achieved significant discrimination in both passive (mean accuracy = 0.92±0.05) and active (mean accuracy = 0.93±0.05) conditions, yielding 100% individual detection rate ( p < 0.001). These results confirm that our paradigm reliably captured early sensory processing in every tested participant. Table 1. Individual sensitivity of ERPs elicitation across conditions Passive 30/30 29/30 30/30 29/30 30/30 Active 30/30 30/30 30/30 30/30 30/30 Passive vs. Active - - - 26/30 28/30 3.1.2 Local effects Group-level analysis of within-pair variations revealed robust MMN and P3a components at Fz electrode across both passive and active conditions (Figure 2.a, second and third columns). For the LocalSF effect (frequency deviants), cluster-based permutation tests revealed negative MMN clusters in both passive (48-236 ms, p < 0.05, peak t = 347 at 148 ms) and active (60-244 ms, p < 0.05, peak t = 369 at 196 ms) conditions, confirming reliable detection of acoustic feature changes. For the LocalSN effect (numerical deviants), the paradigm elicited a more complex response pattern comprising both MMN (passive: 44-176 ms, p < 0.05, peak t = 358 at 144 ms; active: 52-184 ms, p < 0.05, peak t = 160 at 140 ms) and subsequent P3a components (passive: 200-348 ms, p < 0.05, peak t = 564 at 232 ms; active: 192-348 ms, p < 0.05, peak t = 355 at 248 ms). This MMN-P3a complex indicates that numerical deviants engaged both automatic deviance detection and involuntary attention orienting mechanisms. At the individual level, the SVM classification between within-pair deviant and standard stimuli demonstrated high detection sensitivity (Figure 2.b, second and third columns). For LocalSF, 29/30 participants manifested significant MMN responses (p < 0.001), with one participant (participant #2, mean accuracy = 0.57±0.04) in the passive condition falling below the significance threshold (0.60). In contrast, all participants exhibited significant MMN responses in the active condition (p < 0.001). For LocalSN, all participants demonstrated significant MMN-P3a complex responses in both passive (mean accuracy = 0.94±0.06) and active (mean accuracy = 0.95±0.05) conditions (p < 0.001), yielding 100% individual detection rate. These results confirm that within-pair variations reliably elicited automatic change detection (MMN) and involuntary attention orienting (P3a) components across participants. 3.1.3 Global effects For the Global SS-SN effect (numerical deviants disrupting S-S regularity), cluster-based permutation tests at Pz electrode revealed an early negative cluster in both passive and active conditions (passive: 96-180 ms, p < 0.05, peak t = 266 at 148 ms; active: 40-192 ms, p < 0.05, peak t = 219 at 152 ms), followed by a positive cluster that differed between conditions (passive: 196-304 ms, p < 0.05, peak t = 268 at 248 ms; active: 216-404 ms, p < 0.05, peak t = 309 at 284 ms). For the Global SF-SN effect (numerical deviants disrupting S-F regularity), a similar pattern emerged with an early negative cluster (passive: 100-180 ms, p < 0.05, peak t = 224 at 148 ms; active: 104-192 ms, p < 0.05, peak t = 215 at 164 ms) and a subsequent positive cluster (passive: 200-388 ms, p < 0.05, peak t = 377 at 248 ms; active: 216-412 ms, p < 0.05, peak t = 309 at 280 ms). Notably, the positive clusters extended significantly longer in the active condition. At the individual level (Figure 2.b, fourth and fifth columns), for Global SS-SN , 29/30 participants showed significant discrimination in the passive condition (mean accuracy = 0.87±0.06, p < 0.001), with participant #2 (mean accuracy = 0.58±0.03) falling below threshold (0.6). All participants achieved significant discrimination in the active condition (mean accuracy = 0.87±0.07, p < 0.001), yielding 100% detection rate. For Global SF-SN , all participants demonstrated significant responses in both passive (mean accuracy = 0.84±0.07) and active (mean accuracy = 0.88±0.08) conditions ( p < 0.001). The high individual detection rates confirm the robustness of global effects elicitation across participants. Figure 2. ERP analysis of the local and global effect. (a) Group-level waveforms on deviant (red line) and standard (blue line) conditions across the local and global effect in passive and active condition. For P1-N1-P2 complex, the contrast conditions are standard (blue line) and resting state (red line). Shaded areas represent standard error across participants. The color rectangles below the waveform represent the significant difference between conditions ( p < 0.05, cluster-corrected), with color intensity indicating the polarity of difference waves. Topography of the difference waves across different time windows of ERPs in the passive and active conditions. Five effects have specific color bar, with color intensity indicating the polarity and amplitude of difference waves. (b) Individual-sensitivity detection for five effects in passive and active conditions. Red regions represent the accuracy distribution of true label; Blue regions represent the accuracy distribution of randomly permuted label; Black lines represent individual significance thresholds ( p < 0.001, Bonferroni-corrected). 3.2 Differential task effects across ERP components To dissociate voluntary from involuntary attention processing, we directly compared ERP responses between active and passive conditions across all experimental contrasts. Cluster-based permutation tests demonstrated differential task effects across ERP components (Figure 3.a). For early sensory and automatic processing, no significant differences emerged between active and passive conditions for the P1-N1-P2 complex or for MMN elicited by frequency deviants (Local SF ), confirming their pre-attentive nature. However, for Local SN (numerical deviants), significant differences appeared in both the MMN window (184-200 ms, p < 0.05, peak t = 32 at 192 ms) and the P3a window (272-352 ms, p < 0.05, peak t = 53 at 344 ms). Most critically, for global effects, robust differences emerged specifically in the P3b time window for both Global SS-SN (272-392 ms, p < 0.05, peak t = 85 at 348 ms) and Global SF-SN (272-400 ms, p < 0.05, peak t = 93 at 364 ms). These extended positive clusters in the active condition reflect the engagement of voluntary attention processing (P3b) beyond involuntary orienting (P3a). At the individual level (Figure 3.b), classification between active and passive conditions yielded high sensitivity specifically for global contrasts. For Global SS-SN , 26/30 participants demonstrated significant between-condition discriminability (mean accuracy = 0.70±0.06, p < 0.001), achieving 86.67% detection sensitivity. For Global SF-SN , 28/30 participants showed significant discrimination (mean accuracy = 0.71±0.06, p < 0.001), yielding 93.33% detection sensitivity. These results confirm that while early automatic components remained stable across task demands, later attentional components showed significant task-related modulation, particularly in the P3 time window. Figure 3. Contrast on ERPs characteristics between passive and active conditions (a) Group-level difference waveforms between active (red line) and passive (blue line) conditions across the local and global effect. Shaded areas represent standard error across participants. The color rectangles below the waveform represent the significant difference between different conditions ( p < 0.05, cluster-corrected). Topography of the difference waves between active and passive conditions under two levels of global deviants. (b) Individual-sensitivity of the contrast between passive and active conditions under two levels of global deviants. Red regions represent the accuracy distribution of true label; Blue regions represent the accuracy distribution of randomly permuted label; Black lines represent individual significance thresholds ( p < 0.001, Bonferroni-corrected). 3.3 Optimal recording parameters for voluntary attention detection To establish practical recording guidelines, we systematically evaluated how sensor density and epoch number affect the detection of voluntary attention engagement through active-passive discrimination. Analysis across 16 different EEG configurations revealed that discrimination performance was primarily driven by temporal sampling rather than spatial coverage (Figure 4). For Global SS-SN , classification accuracy showed strong positive correlation with epoch percentage (rho Spearman = 0.97, 95% CI: 0.92-0.98, p 0.05). Similarly, for Global SF-SN , performance correlated significantly with epoch percentage (rho Spearman = 0.97, 95% CI: 0.91-0.98, p 0.05). Interestingly, the 32-sensor (mean accuracy = 0.65±0.04) configuration achieved comparable performance to the full 64-sensor (mean accuracy = 0.65±0.04) setup across both global contrasts. These results demonstrate that sufficient temporal sampling is more critical than extensive spatial coverage for reliably detecting voluntary attention signatures. Figure 4. Performance of active-passive discrimination across different EEG configurations under two levels of global deviants Upper panels: Electrode montages of 8, 16, 32 and 64 sensors. Sensors were selected such that they approximated realistic EEG caps respecting the international 10-20 system. Bottom panels: Blue lines represent Global SS-SN effects. Red lines represent Global SF-SN effects. Data are presented as mean with error bars indicating standard error. There are 16 configurations in a 4×4 factorial design: 8, 16, 32, and 64 sensors crossed with 25%, 50%, 75%, and 100% of available epochs (S = 1000Hz standards; F = 1500Hz frequency deviants; N = numerical deviants; sens. = sensor). 4. Discussion This study introduced and validated a paired-stimulus local-global paradigm that addresses the fundamental challenge of comprehensively assessing sequential auditory processing stages while ensuring high individual detection sensitivity within a single experimental session. Our paradigm successfully elicited target components from early sensory processing (P1-N1-P2 complex), automatic deviance detection (MMN) and involuntary attention orienting (P3a) to voluntary attention engagement (P3b), achieving exceptional individual-level detection sensitivity (details in Table 1). Most critically, by contrasting active and passive conditions, we achieved 86.67% and 93.33% individual-level sensitivity in dissociating voluntary from involuntary attention processing for two types of global deviants. Furthermore, we demonstrated that temporal sampling (number of epochs) rather than spatial coverage (number of sensors) primarily determines the reliability of voluntary attention detection, suggesting practical recording parameters for future implementation. Our paradigm’s ability to reliably elicit the P1-N1-P2 complex with 100% detection sensitivity across all participants represents a significant methodological achievement. The temporal and spatial characteristics of these components that align well with established literature (Näätänen & Picton, 1987; Picton et al., 1974). We attribute this high sensitivity to two key design features. First, the fixed first-standard design within all stimulus pairs ensured sufficient trial numbers (1331 ± 24 per participant) to enhance SNR for robust classification. Second, using the pre-stimulus period as baseline (-450 to 0ms before first stimulus) provided clear separation between stimulus-driven responses and resting-state activity. This reliable capture of obligatory sensory responses establishes a solid foundation for interpreting subsequent processing stages, as intact early sensory encoding is prerequisite for higher-order auditory processing. Analyses of local effects revealed an imporrtant dissociation between simple acoustic and complex symbolic deviants. While 1500Hz frequency deviants elicited only MMN in 29/30 participants, numerical deviants consistently evoked both MMN and P3a components with 100% detection rate. This differential response pattern aligns with automatic deviance detection for acoustic feature changes (Näätänen et al., 2007, 2012) versus the dual-processing model where complex symbolic stimuli engage both change detection and involuntary orienting mechanisms (Escera et al., 2000). The absence of P3a for frequency deviants supports the stimulus complexity threshold hypothesis: only deviants requiring higher-order feature extraction exceed the salience threshold for involuntary attention shifts (Conde et al., 2016; Muller-Gass et al., 2007). This neurocognitive dissociation demonstrates that numerical stimuli are essential for comprehensively assessing both automatic and attention-related processes within a unified paradigm. The global effects demonstrated clear task-dependent modulation, providing crucial evidence for the hierarchical organization of auditory attention. In passive conditions, both global contrasts (GlobalSS-SN and GlobalSF-SN) elicited early negativity (96-180ms) and P3a components (196-304ms), reflecting automatic pattern violation detection and involuntary attention orienting. However, extended positive clusters (lasting until generation when voluntary attention was engaged through target counting. This selective P3b enhancement aligns with global neuronal workspace theory, suggesting that conscious access requires both bottom-up salience and top-down attention allocation (Dehaene et al., 2014). Notably, the similar global effect patterns between GlobalSS-SN and GlobalSF-SN conditions suggest that global deviance detection operates at an abstract pattern level, independent of the specific acoustic features (1000Hz vs 1500Hz) that establish the global regularity. The successful dissociation between voluntary and involuntary attention through active-passive contrasts represents a key methodological advance of our paradigm. This robust discrimination at the single-subject level was specifically driven by the presence or absence of P3b, while earlier components remained remarkably stable across task conditions. The P1-N1-P2 complex and MMN to frequency deviants showed no task-related modulation, confirming their truly pre-attentive nature. Even the MMN/P3a complex to numerical deviants, while showing subtle amplitude variations, maintained consistent presence across both conditions. Only the P3b component, reflecting voluntary attention engagement, emerged selectively during active target counting. This finding aligns with previous work demonstrating that passive viewing effectively isolates involuntary processes, while task-relevant processing reliably elicits voluntary attention mechanisms (Bekinschtein et al., 2009; Morlet et al., 2017, 2023). This selective modulation of only the P3b component provides strong evidence for the functional independence of hierarchical processing stages. Such precise dissociation validates our paradigm as an effective tool for probing specific levels of auditory-cognitive processing. Our systematic evaluation of recording parameters revealed that temporal sampling outweighs spatial resolution for detecting voluntary attention. The strong positive correlation between epoch number and classification accuracy (rho = 0.97, p < 0.001) contrasted with the non-significant effect of sensor density. This temporal primacy likely reflects fundamental properties of P3b generation. First, phase-locked averaging across multiple trials progressively enhances ERP SNRs through temporal summation (Cohen, 2014). Second, P3b emergence inherently requires cumulative integration across multiple cognitive cycles, as each trial contributes incremental information to reach reliable discrimination thresholds (Kok, 2001; Polich, 2007). Remarkably, 32-channel configurations matched 64-channel performance, suggesting strategic electrode placement over key generators suffices for capturing P3b dynamics. These findings indicate that clinical implementations should prioritize sufficient trial numbers over dense spatial coverage, potentially reducing setup complexity without sacrificing sensitivity. Two specific limitations of our current design warrant consideration for future optimization. First, our between-session comparison of active and passive conditions cannot fully exclude session-specific effects on attention state or potential carry-over effects between conditions. A within-session design alternating between active and passive blocks could provide more rigorous control. Second, despite successfully reducing protocol duration compared to multi-paradigm approaches, the 40-minute session length may still challenge clinical populations with fluctuating arousal. Notably, our results suggest a potential optimization strategy: since both GlobalSS-SN and GlobalSF-SN showed similar effects, the S-F pairs contributed minimally to the critical active-passive discrimination. Eliminating these pairs could reduce the paradigm to approximately 20 minutes without sacrificing component detection, as numerical deviants alone sufficiently elicit both local (MMN/P3a) and global (P3b) effects. 5. Conclusion As demonstrated in this study, our paired-stimulus local-global paradigm provides a comprehensive and efficient approach for assessing hierarchical auditory processing within a single experimental session. The paradigm successfully captured sequential ERP components from early sensory processing and automatic deviance detection to involuntary attention orienting and voluntary attention engagement, while maintaining high individual detection sensitivity in healthy participants. Most importantly, the robust dissociation between voluntary and involuntary attention through task manipulation demonstrates that different processing levels can be selectively probed within a unified framework. Our finding that temporal sampling density outweighs spatial resolution for detecting voluntary attention offers practical guidance for optimizing recording protocols. This work establishes a methodological foundation for assessing multiple cognitive processing stages efficiently, potentially providing objective markers for evaluating residual cognitive function in behaviorally unresponsive patients. 6. Acknowledgements This work was supported by Science and Technology Planning Project of Liaoning Province (no. 2021JH1/10400049) and Liaoning Provincial Key Laboratory of Intelligent construction IoT Application Technology (2024KFKT-08). Reference Atienza, M., Cantero, J. L., & Escera, C. (2001). 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Collection European Journal of Neuroscience Keywords event-related potentials (erps) local-global mmn p3b voluntary attention Authors Affiliations Chao Guo 0009-0003-2946-620X Dalian University of Technology View all articles by this author Xiaoyu Wang 0000-0002-0828-6328 [email protected] Western University View all articles by this author Zhaonan Ma 0009-0007-8453-5916 Dalian University of Technology View all articles by this author Xiao Yang Dalian University of Technology View all articles by this author Fengyu Cong Dalian University of Technology View all articles by this author Metrics & Citations Metrics Article Usage 222 views 152 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Chao Guo, Xiaoyu Wang, Zhaonan Ma, et al. Concurrent Assessment of Sequential Auditory Event-related Potentials Using an Optimized Paired-stimulus Local-global Paradigm. Authorea . 03 October 2025. 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