Journal of Cognitive Neuroscience

Human long-term memory for visual scenes is remarkably robust, yet the neural mechanisms supporting memory encoding and retrieval remain poorly understood when both processes must operate at the same time. For instance, this might happen when we encounter a familiar place while simultaneously forming new memories of this encounter. We investigated electrophysiological correlates of visual recognition memory using a continuous recognition task (CRT), in which participants judged a continuous stream of scene photographs as previously seen or new, such that encoding and retrieval occurred in parallel on every trial. To make recognition particularly demanding, stimuli were drawn from only four scene categories. Thirty-one participants performed the task while EEG was recorded, and we analyzed canonical ERP markers of retrieval (mid-frontal FN400, 300-550 ms; late parietal effect, LPE, 550-800 ms) and encoding (subsequent memory effect, SME) as a function of stimulus repetition and lag between consecutive presentations. FN400 showed robust old/new effects for both repetitions, whereas LPE differences emerged only at the second repetition. While FN400 amplitude was insensitive to lag, LPE amplitude decreased systematically with increasing lag, mirroring the behavioral pattern of declining accuracy and slower responses. A significant SME emerged selectively for images subsequently recognized on both repetitions, indicating that the SME in continuous recognition is specific for the most robustly encoded items and reflects the strength of encoding. Together, these findings show that canonical ERP markers of recognition memory are preserved even when encoding and retrieval operate concurrently, but their expression depends on how often and how recently an item has previously been encoded - parameters that can be flexibly manipulated within the CRT. This demonstrates that the CRT is sensitive to fine-grained temporal dynamics of memory formation and retrieval that could be missed under standard single-repetition designs.

Cueing paradigms are commonly used to study the neural mechanisms of visual spatial attention control. In these paradigms, each trial starts with an external cue, which instructs the subject to pay covert attention to a spatial location in anticipation of an impending stimulus (instructed attention). Recent work has introduced a new type of cue which prompts the subject to spontaneously decide which spatial location to attend (willed attention). We studied the neural mechanisms of willed attention control by analyzing fMRI and EEG data recorded at two institutions (UF and UC Davis) using the same willed attention paradigm. The findings include: (1) both instructional cues and the choice cue activated the DAN, (2) the choice cue additionally activated a frontoparietal decision network consisting of dorsal anterior cingulate cortex (dACC), anterior insula (AI), anterior prefrontal cortex (APFC), dorsal lateral prefrontal cortex (DLPFC), and inferior parietal lobule (IPL), (3) the decision about where to attend can be decoded in frontoparietal decision network in choice trials but not in instructional trials, and (4) EEG alpha oscillation patterns immediately preceding the choice cue, but not the instructional cues, predicted the postcue direction of attention and the frontoparietal decision network activity. Based on these findings we proposed a model of willed attention control suggesting how the direction of visual spatial attention was decided upon in the absence of external instructions.

According to predictive processing theories, the brain achieves efficiency in perception by comparing current sensory inputs with stored representations of the external world. Previous research has shown that manipulations of expectation can alter neural processing of low-level visual features as well as more complex, naturalistic objects. It remains unclear, however, precisely how the effects of expectancy are altered through learning and changes in stimulus fidelity. Here, we characterised behaviour and neural activity patterns while systematically varying individuals prior exposure to object sequences and the quality of the stimuli therein. Participants viewed rapid image sequences while we recorded their brain activity using electroencephalography (EEG). The stimulus sequences were probabilistically structured such that the appearance of each object was either expected, unexpected, or random. Participants were faster and more accurate in detecting cued target stimuli when these were expected relative to unexpected or random. Multivariate analysis of EEG activity patterns time-locked to the appearance of object images revealed reliably reduced decoding accuracy for both expected and unexpected stimuli relative to random stimuli. These patterns were consistent across exposure and image quality conditions, though exploratory analyses suggested that subtle changes in neural prediction effects may be linked to exposure. The findings do not provide strong support that the brain differentially represents expected versus unexpected object information and suggest that exposure and image quality do not reliably interact with predictive processes in object recognition.

Working memory (WM) is often assumed to play a stronger role in mental operations than in pure storage. However, much of the evidence comes from tasks using novel stimuli requiring active maintenance. Everyday cognition, in contrast, often involves operating on information retrieved from long-term memory (LTM), which may not always require sustained WM storage. Moreover, prior evidence for enhanced WM involvement relies on univariate measures, which cannot separate procedural demands of operations from representational strength of operation-relevant items. Here, we used EEG to test how WM supports mental operations on LTM. First, participants studied color-position associations. Then, on each trial, a color cue prompted retrieval of its associated position, followed by a novel position. Across blocks, participants either performed a mental operation to compute the positions' spatial midpoint or judged whether the probe matched one of the memory positions. Representations of task type and memory position were assessed using MVPA and inverted encoding models on alpha-band power, respectively. Task type was decoded throughout the trial, reflecting persistent task-set representations. In contrast, LTM position was represented in WM more strongly for integration than recognition early in the retention and operation periods, but these differences were transient. These findings challenge the view that mental operations inherently demand enhanced WM engagement: when information is available in LTM, increased WM involvement is transient, not sustained.

Speech comprehension in noisy environments often requires cognitive effort, but listeners may disengage when comprehension becomes impossible. Eye movements have recently emerged as a promising new measure of listening effort, but it remains unclear whether eye movements are sensitive to the full effort profile across easy, difficult, and impossible speech comprehension. Across four experiments, participants listened to sentences at easy, difficult, and impossible levels of multi-talker background babble while pupil size and eye movements were recorded. Pupil size generally followed the expected inverted u-shaped effort profile: low for easy speech, maximal for difficult but still intelligible speech and lower again for impossible speech, although this pattern partly reflected sustained, condition-specific differences and not only sentence-evoked responses. Gaze dispersion - measuring the spread of eye movements - decreased with high temporal selectivity during difficult relative to easy and impossible speech, indicating reduced eye movements during active, effortful listening. However, gaze dispersion was also lower, but less temporally selective, during impossible compared to easy listening, especially in non-baseline-corrected analyses, suggesting that reduced eye movements do not index listening effort uniquely. Instead, eye movements appear to reflect both attentional engagement during difficult listening and disengagement or inward attention when meaningful listening is no longer possible. These findings indicate that pupil size and eye movements provide complementary indices of listening-related cognition, and highlight the integration of listening, cognition, and motor systems.

Social media users often feel that time vanishes while scrolling, but real feeds confound novelty, rewards, social signals, and self-paced control, leaving the driver of this distortion unclear. We tested whether self-paced visual exploration is sufficient to compress subjective time by comparing active scrolling with passive, yoked viewing and a static baseline. Twenty-three adults viewed sequences of natural images under three within-subject conditions: Scrolling (self-paced mouse clicks), Watching (a passive, yoked replay of their own scrolling sequence), and a Baseline (a static image). Participants estimated the elapsed duration of each block. Subjective duration was most compressed under Scrolling (48% of elapsed time), followed by Watching (51%) and Baseline (65%). Two sources separated these effects. Adding back the empty inter-image fixations brought the image-rich conditions to within seconds of the Baseline, showing that observers barely counted the blank gaps; the Scrolling--Watching difference, by contrast, was independent of these shared gaps, isolating self-paced control as a second source of compression. Electrophysiology linked that control to anticipatory neural states and the timing of early visual responses, with no amplified encoding of individual images. The results favor an attention-weighted account of timing, on which subjective duration tracks how much attention reaches the clock, a resource that a self-paced stream and its uncounted gaps both draw away.

Attentional control balances proactive suppression of predictable distractors with reactive suppression of unexpected ones. Yet, how internal states such as alertness shape this balance is unclear. Using pupillometry and eye tracking across two probability-cueing experiments (conducted in 2024) with varying distractor prevalence, we distinguished tonic (baseline pupil size across blocks) from trial-level pupil size fluctuations (trial-by-trial residual variability in pre-stimulus pupil size). With moderate prevalence, suppression of frequent-region distractors developed gradually, whereas high prevalence induced near-immediate suppression. Behavioral measures (e.g., reaction times) were closely linked to tonic and trial-level pupil size fluctuations. Critically, both alertness components jointly influenced control: during early learning, heightened trial-level pupil size increased distractor capture and reduced target fixations, whereas later on, suppression shifted to a proactive mode resilient to trial-level fluctuations. Under high prevalence, this shift occurred faster. Notably, higher trial-level pupil size generally accelerated first target selection. These findings show that tonic alertness and trial-level alertness fluctuations dynamically regulate reactive and proactive control during statistical learning. Impact StatementThis study shows that people become better at ignoring predictable distractions over time, but that this improvement depends not only on what they have learned about the task environment, but also on their current level of alertness. By combining eye tracking and pupil measures, we found that temporary increases in alertness can sometimes help people orient more quickly to relevant information, yet during earlier stages of learning they can also make attention more vulnerable to distracting events. These findings suggest that successful focus in complex environments depends on a dynamic interplay between learned expectations and moment-to-moment fluctuations in mental state, with implications for understanding sustained attention in settings such as monitoring, driving, and other tasks that require people to stay engaged while resisting distraction.

Audiovisual semantic matching can be achieved using either written words or pictures, yet whether these formats engage shared semantic matching representations with similar temporal dynamics remains unclear. We recorded electroencephalography from 27 participants while they performed audiovisual semantic matching tasks in which spoken words were paired with either written words or pictures. Stimuli included both natural and man-made objects. Time-resolved multivariate pattern analyses (MVPA or decoding), cross-decoding, and temporal generalization analyses were used to characterize the temporal dynamics of semantic processing. Reliable decoding of matching versus mismatching judgments emerged in both word and picture conditions. Decoding onset that significant above chance level occurred earlier for written words than for pictures and cross-decoding analyses revealed successful generalization between word and picture formats. Temporal generalization analyses further demonstrated distinct representational dynamics across formats, with word processing characterized by predominantly time-specific neural representations and picture processing showing more sustained and temporally stable representations. In addition, matching-related discrimination emerged earlier for natural objects than for man-made objects across both formats. The results suggest that speech-word matching shows earlier neural evidence of audiovisual alignment than speech-picture matching, potentially reflecting differences in how auditory linguistic input is integrated with visual information across representational formats.

Flexible, goal-directed behavior depends on the ability to select and prioritize information from memory representations freshly encoded from the sensory stream as well as retrieved from previous experience. The spatial gating signatures of internal attention in working memory (WM) are increasingly well characterized, but it remains unclear whether the same neurophysiological mechanisms are recruited for orienting attention to items from long-term memory (LTM). We recorded EEG and eye movements while participants focused on WM versus LTM representations in a unified precision-report task. Retrocues improved performance for both WM and LTM items, but with larger behavioral gains for WM items. Neural and oculomotor markers of spatial orienting, including contralateral posterior alpha suppression and gaze biases toward remembered locations, were robust when focusing on WM items; but were reliably weakened or absent when focusing on LTM items. Multivariate pattern analyses provided complementary evidence for the recruitment of dissociable neural mechanisms when focusing on WM vs. LTM items, which unfolded with similar time courses. Together, the results establish the existence of dissociable neural mechanisms for internal attention, which can be deployed flexibly depending on the relevant memory trace to guide performance. The findings raise interesting and tractable questions about whether differences in representational formats or representational domains drive the distinct internal attention mechanisms.

Previous research on the brain correlates of working memory using functional magnetic resonance imaging (fMRI) and multivariate pattern analysis (MVPA) have shown that neural activity related to information currently needed to respond on a test is considered to be in the focus of attention (FoA). An ongoing controversy pertains to the neural representation of information in working memory that is not needed for the upcoming test but possibly for a subsequent one, which is considered to reside in an activated portion of long-term memory (aLTM). The key theoretical issue regarding aLTM is whether it corresponds solely to an activity-silent neural state. Here, by using a retrospective cuing task in which two arrays of stimuli from different categories were presented in succession on the same trial, and a pattern classifier trained on the first-presented category during the presentation of the second, we provide evidence that aLTM is associated with an active neural state. Specifically, the aLTM effect was demonstrated to be dissociable in direction from that related to the FoA, there was considerable overlap between brain regions representing information in a stronger form in the FoA and a weaker form in aLTM, and the two states appeared to be differentially subject to flexible cognitive control versus natural decay.

Covert spatial attention selects and prioritizes relevant sensory information. Endogenous attention is voluntary, goal-driven, and flexible. However, it cannot alleviate visual polar-angle asymmetries, specifically, the horizontal-vertical anisotropy and the vertical meridian asymmetry. Visual perception is affected by both current sensory inputs and contextual information over time and space, such as the perception of preceding trials. Previous studies reported sequential effects whereby attention interacts with response repetitions. But it is unknown whether and how endogenous attention modulation on performance varies as a function of target location and trial history. Here, we reanalyzed data from three published studies of endogenous attention in orientation discrimination tasks, to (1) assess the typical sequential effects on response, in which response to the current trial is biased toward the previous one, and (2) examine if sequential effects would modulate the performance across locations, across four dimensions: (1) location, (2) feature, (3) attention repetition condition, and (4) the correctness of the preceding (n -1) trial. First, we demonstrated typical sequential effects of response repetition to the repeated location and feature aspects of the target. Second, we found a robust effect of attention on performance, but the results did not reveal evidence of sequential attention effects as a function of the four dimensions in any of the three studies. Moreover, there were no interactions between attention and location when considering trial history. Together, these findings provide compelling evidence that visual polar-angle asymmetries are resistant to endogenous attention, and that even top- down factors-sequential effects-do not alleviate these asymmetries in performance.

Language comprehension involves the integration of single words (lexical units) into phrases and sentences (multi-word structures). Previous frequency-tagging studies have found that low-frequency neural responses synchronize to the frequency of multi-word structures. However, it is currently unclear how exactly structural and lexical processes jointly impact these synchronization findings. The present magnetoencephalography experiment implemented the frequency-tagging paradigm in the visual modality with written words to investigate neural synchronization to multi-word sentences varying in internal structure (reversed word orders between verb-initial Spanish and verb-final Basque sentences) and in lexical content (real words and pseudo words). We find converging evidence that neural responses largely synchronize to structural rather than lexical features. This was observed as robust phase synchronization strength to the frequency of sentences containing reversed structures, with certain lexical modulations depending on language-specific structural features. Crucially, we also found shifted phase angle dynamics between the reversed structures of Spanish and Basque sentences independently of word-level lexical characteristics. Together, these findings suggest that neural synchronization to multi-word structures is largely driven by distinct structural features operating via two segregated neural dimensions: frequency coding for the coarser aspects (i.e., timescale/duration) and phase representing the finer-grained aspects (i.e., internal structure) of multi-word structures. Our findings thus advance key insights into the core components of the neural mechanisms supporting language comprehension. HighlightsO_LINeural synchronization to sentences is driven by structural (not lexical) features. C_LIO_LIRobust sentence-frequency synchronization across languages varying in structure. C_LIO_LIPhase angle is selectively sensitive to cross-linguistic structural differences. C_LIO_LILexical modulations depend on language-specific structure. C_LIO_LIStructure synchronization segregates into two dimensions: frequency and phase. C_LI

How the brain constructs meaning across extended contexts remains poorly understood. While neural responses to words and sentences are well characterized, much less is known about the brain mechanisms supporting narrative comprehension. Sentence-level studies suggest that neural activation increases as word meanings are integrated into sentence meaning. At the discourse level, theories propose that narratives depend on situation models, possibly engaging networks beyond core language regions, including the default mode network. Because narrative comprehension unfolds over longer timescales, processing time may be a bottleneck. In this MEG study, we tested how representation size and presentation rate shape neural responses by varying linguistic structure (words, sentences, stories) and the speed of visual text in 1-4-word chunks. We found an early bilateral story effect in visual cortex, followed by a spatiotemporal progression of activity along the temporal lobes that culminated in a three-way contrast among word lists, sentence lists, and stories. Faster presentation altered this pattern: the left-lateralized story effect disappeared, and the right-lateralized effect became more spatially restricted. Under Fast presentation, significant effects were limited to left lateral language cortex distinguishing coherent inputs from word lists, and to two right-hemisphere story effects in extended language regions. We also observed a context effect in the Slow Story condition, with neural responses remaining constant as the narrative unfolded while they increased in the SentenceList and WordList conditions. This effect was absent under Fast presentation, suggesting story-specific comprehension that is temporally constrained. Together, the findings identify temporal constraints as a key determinant of the neural signatures of narrative processing.

Our visual environment can be parsed into objects and scenes, a distinction that is reflected in the organization of the human visual cortex. Previous research has shown that object and scene perception nevertheless closely interact, such that scenes influence object perception and objects influence scene perception. It remains unclear, however, whether and how objects that are not inherently diagnostic of their surroundings aid the recognition of poorly visible scenes (e.g., a person standing in a dark living room). Here, in three behavioral experiments, we show that participants made more accurate indoor/outdoor judgments when degraded scene photographs were presented together with an object than when the scene or the object was shown alone, even though the same object categories appeared in indoor and outdoor scenes. This object-driven benefit vanished once scene structure was removed through phase scrambling and was reduced when objects appeared in physically inconsistent locations within the scenes. These results suggest that objects in consistent locations (e.g., a person standing on a floor) disambiguate scene layout. Finally, in a pre-registered transcranial magnetic stimulation (TMS) study (N = 48), we provide causal evidence that the object-selective lateral occipital cortex (LOC) supports scene categorization when scene layout is disambiguated by within-scene objects. Stimulation of the LOC, particularly at 260-300 ms after stimulus onset, selectively disrupted object-based scene recognition. Together, these findings demonstrate that objects facilitate the read-out of the surrounding space in service of efficient scene recognition. Significance StatementUnderstanding how scene and object processing interact for efficient recognition is a key question in natural vision. Research has long emphasized how surrounding scenes help us identify objects, yet the reverse - how objects shape the perception of scenes - has received little attention. In the dark, does a glimpse of a floating boat tell us we are looking at a lake? In this study we demonstrate that a single object helps people recognize hardly visible scenes. This benefit required intact scene structure and depended on where the object appeared in the scene. In addition, object selective visual cortex was causally related to this benefit. Together, these findings show that objects visual appearance can be used to better understand our surroundings.

Automation has been shown to weaken the sense of agency (SoA), the experience of controlling ones actions and their outcomes, by disrupting the predictive link between intention and effect. Explainable AI (XAI) has been proposed as a solution, yet the neurocognitive mechanisms through which explanations restore agency remain unclear. Across three EEG experiments using an autonomous-driving paradigm, we examined how automation and different forms of AI explanations modulate explicit agency judgments and early neural markers of agency-related predictive processing. In Experiment 1, automation reduced explicit feelings of control and was associated with reduced sensory attenuation, as reflected by increased P1-N1 amplitudes, decreased N1-P2 amplitudes, and delayed N1 latencies. In Experiment 2, distal (goal-level) explanations partially restored agency and selectively modulated early auditory responses, decreasing P1-N1 and increasing N1-P2 amplitudes. In Experiment 3, combining distal and proximal (trajectory-level) explanations produced the strongest behavioural and neural restoration of agency, yielding a graded attenuation of P1-N1 and enhanced N1-P2 responses along with accelerated N1 latencies. Across all experiments, mismatch negativity (MMN) remained unaffected, indicating that pre-attentive deviance detection is preserved regardless of agency or explainability. Together, these results identify component-specific EEG markers that track fluctuations in the sense of agency and demonstrate that multi-level intention sharing by AI systems enhances both predictive engagement and explicit control experience. This work provides a neurocognitive foundation for designing explainable autonomous systems capable of maintaining user agency.

Serial dependence is influenced by sensory uncertainty and contextual continuity, but it remains controversial whether these influences reflect separate mechanisms or different expressions of a shared updating process. Across two time reproduction experiments (N = 44), we examined how motion coherence and coherence transitions modulated the attraction of recent temporal history while controlling for central tendency effects from the current stimulus. In Experiment 1, the low coherence led to stronger serial dependence compared to the high coherence. In Experiment 2, enhanced coherence categories introduced salient contextual boundaries; serial dependence was markedly stronger on the same category transition than switch transition. A three-state Kalman filter model, comprising fast (serial dependence), slow (central tendency), and bias (decision carryover) states captured these patterns through coherence-dependent modulation of fast-state process noise and Kalman gain. Within the tested model space, this precision-weighting account was selected in both experiments; with little evidence that an explicit state reset was needed. These findings support the precision-weighted updating account in which recent history is weighted according to the reliability and stability of the current perceptual environment.

Memorizing a new phone number or address is hard at first, but becomes easier with repetition, as information shifts from working memory to long-term memory. Here we investigated how repetition affects the storage and transition of different aspects of mnemonic information by comparing univariate neural markers of active object storage with multivariate decoding of memory content. Thirty participants encoded lateralized stimuli from a continuous shape space into memory. Memory items were repeated six times in a row to induce learning. In line with earlier work, EEG recordings revealed that repetition led to a reduction in contralateral delay activity (CDA), a measure of active storage that has been taken to reflect a pointer-like representation of the individual object or its original source. In contrast, shape decoding during the retention and also after an impulse perturbation remained constant across repetitions. These results suggest that learning over repetitions reflects the abolishment of active and individuated object memory representations while passive, source-independent memory representations are retained.

During speech comprehension, the brain dynamically infers a hierarchy of increasingly abstract representations from the sensory input. An important step in the inferential hierarchy is the combination of words to form phrases and sentences. Whether this process is driven primarily by statistical patterns in the linguistic input, or by a mechanism that combines words into hierarchical representations, is a subject of considerable debate that has regained importance with the arrival of large language models. This study investigates whether local cortical activity (high gamma power; 70-150 Hz) from intracranial recordings is jointly modulated by lexical probability and syntactic structure; and whether lexical probability affects the inference of syntactic structure. To this end, an open dataset of electrocorticography recordings is analyzed with multivariate temporal response functions and a model comparison approach. The results indicate that high gamma power is sensitive to multi-word estimates of constituency structure and lexical probability estimates, both in isolation and jointly. The temporal response functions suggest that syntactic structure building depends on interregional communication between regions connected through dorsal- and ventral streams. Furthermore, the study provides evidence that bottom-up syntactic information is less likely to be encoded by neural populations that strongly code for lexical probability measures, while top-down syntactic information shares neural resources with lexical uncertainty. We suggest that lexical uncertainty modulates the weighting of anticipatory structural information. With this, the current study supports models that suggest that cues are leveraged flexibly in a feed-forward and feed-back fashion during speech comprehension.

Languages vary in whether and how they encode gender. As societies pursue greater inclusiveness, gender-inclusive language (GIL) has emerged as a debated innovation, introducing pronouns and morphological strategies to neutralize grammatical gender (e.g., todxs, for todos/todas, "all"). Yet whether GIL actually reduces gender expectations remains empirically underexplored. Evidence at the neural level is especially scarce. To address this gap, we asked Italian speakers to categorize masculine (lui, "he") and feminine (lei, "she") pronouns following nouns with canonical (masculine -o, feminine -a) or neutralized endings (-*, -{schwa}). Noun gender-stereotypical association was independently manipulated (male-oriented, e.g., chirurgo/a/{schwa}/*, "surgeon"; female-oriented, e.g., maestra/o/{schwa}/*, "teacher"; neutral, e.g., vicina/o/{schwa}/*, "neighbor"). Recording response times and event-related potentials (ERPs) to target pronouns allowed us to assess their automatic integration and processing costs. Gender-incongruent pronouns after canonical forms elicited longer response times and larger N400 and P300 amplitudes, reflecting increased processing difficulty and reanalysis. Pronouns following GIL forms showed an intermediate processing profile. Response times fell between consistent and inconsistent conditions, N400 amplitude was larger than in the consistent condition, and P300 amplitude was reduced compared to the inconsistent condition. Together these findings indicate that both pronouns remained viable interpretations and could ultimately be integrated. Stereotype-based knowledge shaped early processing without preventing integration, predominantly for masculine pronouns. Overall, our findings provide the first neural evidence that, despite processing costs, GIL forms can foster gender-neutral representations, with relevance to ongoing societal debates and broader cross-linguistic implications.

Aperiodic neural activity (1/f EEG) has been proposed to reflect the balance between excitatory and inhibitory (E/I) inputs, with steeper spectral slopes reflecting increased inhibition and flatter slopes indicating excitation. This activity is also thought to reflect the temporal coordination of neural firing, offering insights into fundamental brain dynamics. Recent studies have shown that the 1/f slope is sensitive to stimulus onset, characterized by initial inhibitory shifts followed by excitatory rebounds, which may reflect cognitive control mechanisms involved in suppressing distractions and preparing goal-directed responses. However, previous research has relied on fixed temporal windows and insufficient control of ERP contamination, limiting our understanding of rapid control dynamics. Here we used newly developed time-resolved analyses to study 1/f spectral slope modulation during a Picture-Word Interference task, focusing on two canonical cognitive control markers: the Congruency Effect (CE) and Congruency Sequence Effect (CSE). Forty-nine participants categorized pictures while ignoring congruent or incongruent words. Behaviorally, we replicated robust CE and CSE patterns. Spectral slope analyses showed that incongruent trials elicited steeper slopes -- consistent with increased inhibition -- particularly in frontal and central regions, reflecting conflict-related control engagement. Moreover, CSE analyses revealed dynamic slope modulations across frontal, central, and occipital components over time, suggesting control adjustments influenced by previous trial congruency. These results provide the first within-trial time-resolved evidence that aperiodic 1/f EEG activity can track both immediate conflict resolution and cognitive adjustments, offering a temporally sensitive neural marker of cognitive control, albeit with effects that are small in magnitude on average.