Psychonomic Bulletin & Review

When we feel restless and easily distracted, continuously switching tasks (exploration), our pupils tend to be large. In contrast, when we are calmly focused on a single task (exploitation), our pupils tend to be small. According to the Adaptive Gain Theory (AGT), a switch from exploitation to exploration is associated with an increase in norepinephrine in the locus coeruleus, which in turn triggers pupil dilation. However, the AGT does not provide a functional explanation of why exploration triggers pupil dilation. One possibility is that visual sensitivity, which increases with pupil size, is especially important during exploration. We set out to provide evidence consistent with this functional explanation, as well as to replicate two key previous results. Participants performed a four-armed bandit task, which induces both exploration and exploitation behavior. During the task, participants also needed to detect an occasional and unpredictable near-threshold peripheral flash. We replicated two key results: pupils were larger during exploration than during exploitation; and increased pupil size (overall, independent of exploration status) was associated with increased visual sensitivity. However, most importantly, we did not find that visual sensitivity was higher during exploration than during exploitation; probably, the reliable-yet-tiny increase in pupil size during exploration was too small to affect visual sensitivity. We conclude that key previous results are replicable; however, common experimental paradigms, such as the four-armed bandit task, induce only small changes in exploration behavior. Therefore, more powerful paradigms are required in order to test functional explanations of pupil-size changes during exploration and exploitation.

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.

Summary paragraphA hallmark of learning is the need for sensory stimuli (Ginns, 2015; McGraw et al., 2009; Reinwein, 2012; Spence, 1950) so that learning is fundamentally based on sensory input signals affecting behaviour, physiology, and neurology. If behavioural measures of learning can be causally linked to physiological and neurological variables, a broader understanding of the mechanisms related to learning in schools, learning disabilities, and learning and health issues may emerge (McGraw et al., 2009). Despite decades of research on the physiological/neurological variable of sympathetic activation, learning, and achievement (Horvers et al., 2021), any causal relation remains unclear (Cowley et al., 2014; Mason et al., 2020; Pijeira-Diaz et al., 2016; Sung et al., 2023; Yu et al., 2024) and issues with instrument validation remain (Costantini et al., 2023; Hu et al., 2024; Milstein & Gordon, 2020; Van Der Mee et al., 2021). Here we investigate the effect of sensory input on sympathetic activation by using validated instruments for skin conductance measurement (Batista et al., 2019) and whether sympathetic activation is connected to learning in a cognitive laboratory context and an ecologically valid classroom context. In both contexts, we found a physiological variable which correlated with learning and that sensory input affected this variable while student movement did not. These sensory inputs varied depending on the different instructional activities the students participated in. Together, these findings bring us one step closer to a model linking sensory input to behavioural, physiological, and neurological variables.

Iconicity in spoken language refers to the mapping of speech sounds to meaning. For example, the pseudoword "bouba" is judged to sound rounded, whereas the pseudoword "kiki" is judged to sound pointed (Ramachandran & Hubbard, 2001). Recent work has found systematic relationships between speech acoustics and iconicity ratings in various meaning domains, including shape. To control for confounding by semantic knowledge, much research on iconicity relies on pseudowords. However, the role of iconicity in conveying the meanings of real words is still poorly understood. Here, we compared the relationship between speech acoustics and shape iconicity ratings for both pseudowords and real words. In this experiment, participants rated real words and pseudowords for how rounded or pointed they sounded. We compared the relationship between 12 acoustic parameters and the rounded/pointed ratings for both words and pseudowords. We found that the correlations between these acoustic parameters and the ratings were similar for real words and pseudowords, providing key evidence that iconicity of real words is linked to speech acoustics.

During typical development, non-social visual object recognition emerges in the first year of life, engaging low-level visual cues and higher-level mechanisms involving inference and prior knowledge. How these processes function in minimally verbal autism (mvASD) remains poorly understood. We studied children with mvASD (n=22, 6-11 years) using touchscreen-based oddball and contour-detection tasks targeting low-level stimuli (e.g. shape and orientation), and mid-level stimuli (e.g. illusory Kanizsa contours and 3D shapes). Pointing and eye-gaze responses were measured. Typically developing children (n=22, 6-12 years) served as a reference group. Accuracy and reaction-time profiles among mvASD participants were heterogeneous across experimental visual tasks and standardized developmental measures. All mvASD participants detected targets in the easiest condition, and approximately half succeeded across low-level tasks. Overall performance declined with increasing visual complexity, consistent with attenuated inference-based processing; communication ability and nonverbal reasoning together accounted for approximately 69% of between-participant variance in visual task performance. Critically, exploratory analyses suggested systematic perception-action dissociations rather than random error. First, the majority of participants who failed to point correctly (n=9) reliably fixated the correct target. Second, in the Kanizsa oddball task, nearly half of successful mvASD participants pointed to local inducers rather than the illusory figure center, unlike TDs. Third, more participants showed within-age-range nonverbal reasoning performance on Ravens colorful progressive matrices when responding by puzzle placement than by pointing. These converging findings challenge interpretations of mvASD performance as reflecting perceptual or cognitive capacity alone, suggesting visual signals may guide action selection differently in mvASD. Lay SummaryMinimally verbal children with autism showed individual differences in visual processing tasks. While developmental measures like communication ability and reasoning skills predicted most of the variation in performance, exploratory observations revealed an intriguing pattern: the same children sometimes succeeded when using their eyes to indicate answers but failed when pointing or performing better when placing puzzle pieces than pointing in a booklet to identical visual display. Several children who correctly detected illusory triangular shapes consistently touched the corner pieces rather than the triangle centers. These patterns suggest that performance depends not only on developmental and visual perceptual abilities, but also on how children are asked to respond. Parents and educators should consider: might a child who fails a pointing-based test succeed with a different response method?

Response inhibition, the ability to suppress contextually inappropriate actions, is a cornerstone of cognitive control and is commonly assessed using paradigms such as the go/no-go task. However, traditional go/no-go paradigms rely on binary outcomes such as commission errors, which offer limited insight into the dynamic, graded behavioral adjustments underlying successful stopping. The present study developed a novel mouse-tracking go/no-go paradigm with a dynamic start to capture inhibitory processes during ongoing execution. Twenty-three healthy young adults completed the task in two sessions separated by approximately one week to evaluate the test-retest reliability of standard behavioral measures (error rates and reaction times), and three kinematic features: path length, mean velocity, and mean acceleration. Results revealed robust differences between go and no-go trials across all measures. Successful inhibition was characterized by significantly shorter path lengths and reduced mean velocity and acceleration compared to go trials. Critically, all measures demonstrated moderate-to-good test-retest reliability across sessions, with intraclass correlation coefficients ranging from .75 to .85 for go trials and from .59 to .83 for no-go trials. These findings establish construct validity and psychometric reliability of the current mouse-tracking go/no-go paradigm. The demonstrated stability of these measures provides the methodological foundation for their use in cross-sectional, longitudinal, and intervention research targeting inhibitory control.

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.

Pupillometry provides an objective way to index effort across domains. However, pupil size is strongly affected by luminance changes, which can obscure effort-related effects, and limit its use in most applied scenarios with dynamic visual input. We here introduce and validate a method to overcome this problem. To this end, participants performed an auditory n-back task of differing difficulty while viewing either constant visual input or dynamic driving movie clips. Effort was assessed physiologically (pupil size), behaviorally (accuracy), and subjectively (NASA-TLX). Accuracy, questionnaire scores, and pupil size were analyzed at the session level, while pupillometry additionally provided continuous time-resolved information. As expected, pupillometry tracked differences in effort, but its discriminability was substantially reduced under dynamic visual input. Correcting for the effects of overall luminance and moment-to-moment luminance changes using a dynamic, explainable, and open-source modeling procedure (Open-DPSM) considerably improved effort discriminability on both aggregate and time-resolved levels. At the aggregate level, luminance-corrected pupillometry slightly outperformed accuracy and NASA-TLX. Combining all three measures yielded the highest classification performance (AUC = 0.98), supporting the view that effort is multifaceted and best captured multimodally. These findings establish a practical basis for fine-grained physiological tracking of effort and arousal in both fundamental and applied research using complex, dynamic stimuli. A tutorial section guides researchers in applying luminance correction to their own pupillometric data in dynamic viewing environments using the here validated approach.

Inhibition of return (IOR) refers to the slowing of response times (RTs) for stimuli presented at previously inspected locations relative to novel locations. However, the exact processing stage(s) at which IOR occurs, and its nature across different response modalities, remain debated. By reanalyzing RT data from a target-target IOR paradigm with a single noisy accumulator model, we tested whether IOR could occur at sensory or attentional stages of processing, or at later stages of decision and action selection. We considered IOR under two conditions: manual and saccadic responses. The within-trial Gaussian noise parameter best explained both manual and saccadic IOR, suggesting that in both modalities, IOR may result from a more fluctuating accumulation of evidence for repeated locations. These results support the hypothesis that target-target IOR may primarily involve attentional-level mechanisms. Significance statementWe respond more slowly to a stimulus that is presented within a short interval in the same location ("inhibition of return"), a bias thought to promote efficient visual exploration. Using evidence-accumulation modeling of manual and eye-movement reaction times from two previous studies, we found that the key change linked to inhibition of return is greater within-trial variability (noise) in evidence accumulation, not a higher decision threshold. Understanding which processing stage is affected can help connect behavioral effects to the brain networks that support attention and orienting.

Current debates regarding the relative contribution of saliency versus semantics to gaze control often rely on comparing the predictive power of saliency and meaning maps. We argue that such indirect, global approaches are fundamentally limited because fixations arise from heterogeneous, local causes that are conflated in whole-scene comparisons. To substantiate this claim, we used a direct method where participants explicitly identified the reasons for fixation at specific clusters of high fixation density, distinguishing between low-level saliency and various semantic categories, as well as the most important one. The obtained judgments revealed that multiple factors contribute simultaneously to gaze control. Although their influence varied across fixation clusters, semantics generally dominated saliency. Notably, abstract semantic categories, particularly "unknown/unusual," proved important, highlighting the role of prior knowledge and novelty besides personal relevance in guiding attention. To interpret these findings in the context of existing models, we propose a framework distinguishing between processes highlighting interesting locations in the image from a sampling strategy translating this information into scanpaths. Within this framework, classic saliency and meaning maps are viewed as restricted inputs to the strategy, whereas deep learning-based models (e.g., DeepGaze IIE) are more general and may also implicitly encode aspects of the strategy itself. Consistent with this, we found that the predictive performance of DeepGaze IIE varied less significantly with the specific reasons for fixation than that of classic saliency and meaning map approaches.

During active vision, the brain must coordinate where to move the eyes with predictions about upcoming sensory input. Before each saccade, perception is enhanced at the upcoming fixation location, but whether this enhancement depends on expectations about target features remains unknown. Here, participants prepared a saccade to a cued location while reporting the presence and orientation of a brief visual target that appeared either at the saccade goal or at the opposite location. Feature expectation was manipulated across blocks by varying the probability of the two target orientations. Perceptual sensitivity (d') increased when targets were presented at the saccade goal, consistent with presaccadic enhancement, and was also higher for less expected features. However, these effects were independent: feature probability did not alter the magnitude of presaccadic enhancement. Moreover, presaccadic enhancement increased near saccade onset, whereas the advantage for less expected features weakened as movement onset approached. Saccade latency revealed a contrasting pattern. Visual targets presented at the saccade goal delayed movement initiation. This delay depended on feature probability, with longer latencies for unexpected than for expected features only when saccades were directed towards the target. This location-specific effect persisted after accounting for perceptual report, and the latency cost for unexpected features was reproduced in a follow-up experiment. Together, these findings show that feature probability enhanced sensitivity to unexpected information independently of presaccadic enhancement, while selectively delaying saccade initiation towards targets with unexpected features. This dissociation suggests that feature expectation modulates perception and action through functionally distinct forms of visual processing.

Flow state, characterized by optimal engagement and performance, represents a key concept in understanding human performance and cognitive resource allocation. Grounded in Csikszentmihalyis and Sherrys flow theory and the Limited Capacity Model of Motivated Mediated Message Processing (LC4MP), this study investigated physiological and neural correlates of flow state during a simulated driving task under different music conditions and difficulty levels. Using a 2 x 3 factorial design with 20 participants, this study examined self-selected versus non-self-selected music across three difficulty levels, testing the relationship between task switching, cognitive resource allocation, and flow state. Physiological measures included heart rate and EEG (alpha/theta power) using a 4-channel Muse 2 headband, alongside a self-report measure of flow experience. Hierarchical linear modeling revealed significant physiological changes during self-selected music: heart rate decreased ({beta} = -5.15, p < .001), while alpha ({beta} = 5829.77, p < .001) and theta power ({beta} = 7637.24, p < .001) increased. Task difficulty also showed significant effects, with heart rate decreasing during hard ({beta} = -6.70, p < .001) and moderate ({beta} = -3.40, p = .001) conditions. In particular, while physiological measures showed robust changes, the self-reported flow state did not reach significance. Task switching rates showed significant decreases during self-selected music ({beta} = -0.86, p < .001) and hard difficulty ({beta} = -0.61, p < .001), supporting the LC4MP frameworks predictions regarding cognitive resource allocation. These findings demonstrate how task switching and cognitive resource allocation relate to flow state induction. The results highlight the importance of multimodal measurement approaches and demonstrate that personal relevance through music selection and task difficulty significantly influence physiological and neural responses during performance. Future research should employ more comprehensive measurement approaches to better capture the complexity of flow-related neural activity and its relationship to task switching and cognitive resource allocation.

Motion perception depends on estimating the relative timing of sensory events under internal uncertainty. Although perceptual uncertainty is commonly represented by a single internal noise parameter, its structure, sources, and temporal organisation remain poorly understood. Here, I investigated the computational structure of internal uncertainty in phase-based tactile motion perception using continuous amplitude-modulated vibrations delivered simultaneously to two fingertips. Motion discrimination accuracy, response latency, confidence, and confidence entropy exhibited systematic phase-dependent changes, revealing distinct behavioural signatures of temporal uncertainty. Computational analyses demonstrated that tactile motion perception is not explained by a single source of landmark timing uncertainty. Instead, behavioural performance was best accounted for by two additive uncertainty components: an amplitude-dependent component associated with extracting temporal landmarks from the vibration envelope, and an amplitude-independent component shared across stimulus conditions. This dual uncertainty framework consistently explained the frequency dependence of motion perception, the reduced uncertainty observed for sharper vibration envelopes, and the previously reported enhancement of motion perception with exponential compared with sinusoidal modulation. An independent temporal order judgement experiment further validated the uncertainty parameter inferred from motion discrimination, demonstrating that sharpening temporal landmarks reduced timing uncertainty by 35%. Finally, manipulating the initial stimulus state showed that perceptual choices followed the temporal sequence and correspondence of landmark events rather than the initial evolution of the vibration envelopes, providing independent support for landmark-based computations. these findings demonstrate that tactile motion perception is governed by multiple computational sources of landmark timing uncertainty and establish phase-based tactile motion as a tractable paradigm for independently measuring, manipulating, and modelling the computational structure of perceptual uncertainty underlying sensory decisions.

The ability to orient or attend to sensory events is generally greater in response to visual and auditory cues occurring together than in response to single-modality cues occurring alone. In such cases the perceptual fusion of cross-modal stimuli (multisensory integration) depends on low-level features (e.g., location, intensity) and follows well established principles. However, less is known about multisensory integration mechanisms when behavioral responses are less direct and require top-down control. Here we investigate this in human participants using an urgent multisensory choice task that effectively dissociates stimulus-driven and goal-driven contributions to performance based on their distinct temporal signatures. Task conditions varied the modality of the cues (auditory, visual, or both), their location (left or right), and the rule defining the correct choice (look toward or away from a given cue). When spatially coincident cues were associated with the same response rule ("look away"), we observed multisensory enhancement and performance remained close to a statistical expectation as the choice process unfolded. However, when spatially disparate cues were associated with different rules but the same target, one cue dominated performance and the other produced crossmodal capture, i.e., low-level competition. The results indicate that the efficacy of multisensory integration is dictated by the stimulus-and goal-driven signals produced by each cue, with all four factors rapidly interacting in accordance to the dynamics of spatial attention. Significance StatementAuditory and visual stimuli located near each other in space and time are typically bound into a single sensory percept that draws attention most effectively. However, it is unclear whether such "multisensory integration" occurs during behaviors that go beyond directly attending or orienting to cue stimuli and require top-down control. We investigated this using a novel task design with which stimulus-driven and goal-driven contributions to performance can be accurately identified. We found that multisensory enhancement depends not so much on the complexity of the requested cue-response associations, but rather on the timing and alignment of the stimulus-and goal-driven signals derived from each cue (auditory and visual) -- similar to the way that such signals dictate the allocation of spatial attention.

Visual search is a critical component of many professions such as military operations, baggage screening, and radiology. Aided Target Recognition (AiTR) systems are designed to highlight potential threats across the operator visual field in real-time, directing attention and improving accuracy. However, these systems may impact search and, consequently, situational awareness by diverting attentional resources from non-highlighted, yet relevant, locations. Previous work suggests that scene gist is extracted within the first 250 ms of scene onset (Vo & Henderson, 2010). As such, this study examined whether a 250 ms AiTR onset delay could encourage a more even distribution of attention. Participants searched synthetically generated scenes and classified each person in the scene as armed or unarmed. Depending on their condition, participants either saw the scenes unaugmented (No AiTR condition), with AiTR highlights consisting of red bounding boxes around armed people and yellow boxes around unarmed (AiTR condition), or with AiTR highlights presented 250 ms post scene onset (Delayed AiTR condition). A surprise memory test of background objects presented in the search scenes was administered to all participants upon completion of the search task. As predicted and preregistered, results showed less overt attentional deployment to background information (anything other than the people themselves) in the AiTR condition compared to No AiTR , however, decreased overt attentional deployment was not seen in the Delayed AiTR group. A similar pattern was observed in the memory data (with the AiTR condition having a lower score than the No AiTR condition and the Delayed AiTR condition), this difference was not significant.

During explicit sequence learning (ESL), micro-offline gains (MOGS) occur during brief rest periods. MOGS are calculated as the difference in keypresses-per-second (KPS) between the first sequence of one trial and the last sequence of the preceding trial. To date, all studies evaluating MOGS have calculated KPS from the motor execution time (MET) that occurs between keypresses, but this approach ignores potential contributions from motor preparation which occur prior to the first keypress. Given that ESL relies on both pre-movement motor planning and subsequent motor execution, we hypothesized that ignoring motor preparation time (MPT) neglects a critical component of skill acquisition, potentially misrepresenting the true magnitude of MOGS. To test this, we calculated MOGS with and without MPT in thirty adults who performed an ESL task. Our results show that including MPT flipped MOGS from positive to negative and significantly increased the positive correlation between early learning and a gold-standard ESL metric: the number of correct sequences performed. Our results suggest that MPT should be incorporated into MOGS calculations and that excluding it overestimates micro-offline learning.

Context effects are ubiquitous across sensory systems and reflect a general encoding principle for both simple and complex stimuli. One simple context effect, contraction bias, manifests in two-interval perception tasks as a bias of the perceived magnitude of the first stimulus toward the center of the overall magnitude range. The underlying cause of contraction bias is unclear. One explanation is that a listeners magnitude estimate of the first stimulus is combined with a perceptual anchor, usually the mean stimulus magnitude, biasing it toward the anchor (sensory model). An alternative explanation is that a listeners response criterion shifts, based on the magnitude of the stimulus pair, relative to the mean magnitude of the stimuli range (decision model). Two pitch-discrimination experiments were performed to test these hypotheses in the auditory domain. The first was a forced-choice discrimination task, where listeners were asked to identify the higher or lower tone in a pair. The second was a same-different task where listeners indicated whether or not the two tones in a pair differed in frequency. Contraction bias was observed in the higher-lower discrimination task, even after extensive perceptual training with feedback. In contrast, no contraction bias was observed in the same-different task. Computational models of the sensory and decision hypotheses were fit to data from both experiments. The sensory model captured the pattern of results the higher-lower experiment but erroneously predicted a contraction bias in the same-different task. The decision model produced similar predictions to the sensory model in the higher-lower task but correctly predicted no contraction bias in the same-different task, and produced lower prediction errors and more stable parameter estimates in both paradigms. Overall, the results suggest that the underlying nature of the contraction bias may reflect decision, rather than sensory, biases based on the context.

Internal forward models predict the sensory consequences of motor commands; however, whether the anticipated availability of post-action feedback contributes to the precision of the action itself remains unknown. We manipulated the predictability of post-release visual occlusion in skilled basketball players. Participants performed three-point shots while wearing liquid-crystal shutter goggles. The study tested three conditions: a no-occlusion baseline, certain-occlusion condition in which players knew that their vision would be occluded at ball release in every trial, and random-occlusion condition in which they could not predict whether an occlusion would occur. Shooting accuracy declined in the certain-occlusion condition relative to the no-occlusion condition (49.2% vs 41.7%). The random-occlusion condition did not differ from the baseline (46.1%). Within the random condition, the accuracy in occluded trials were virtually identical to that in non-occluded trials (46.6% vs 46.2%), even though the immediate visual occlusion was the same as in the certain-occlusion condition. These results demonstrate that it is not the absence of post-action information per se that disrupts motor execution, but the prior certainty that action consequences will be unavailable. We interpret this finding as a prospective influence of anticipated consequence loss, whereby motor execution depends on whether the prediction-outcome loop remains closable.

Studying chess experts helps researchers understand how intensive practice shapes thinking skills. Cognitive flexibility is the ability to adjust thoughts when rules or tasks change. Working memory is the ability to hold and use information over short periods. This study compared cognitive flexibility and working memory precision between adolescent chess players and non-players. Twenty-four professional chess players and twenty-five controls completed two novel behavioral tasks. Chess players showed better accuracy in both tasks than controls. They adapted more efficiently when rules changed during a continuous learning task. They also remembered facial expressions more precisely in a working memory task. Learning rates in the flexibility task did not differ between groups. These results indicate that chess expertise may improve rule-guided flexibility and visual working memory precision in adolescents.

Numerosity adaptation (the underestimation of number after exposure to a numerous adaptor) is reduced when adaptor and test differ in color, suggesting that the numerosity system parses items into color-defined categories. Here we ask whether this chromatic selectivity is organized into multiple narrowly tuned chromatic channels, and whether its expression depends on individual chromatic sensitivity. Twenty observers (aged 22-61) completed two psychophysical tasks. First, chromatic discrimination was measured for five hues spaced in 5{degrees} CIE L*a*b* steps ({Delta}H = 0{degrees}, 5{degrees}, 10{degrees}, 15{degrees}, 20{degrees}) from a red reference (LCh: 54, 118, 38), yielding an individual just-noticeable difference (JND). Second, numerosity adaptation was measured across the same five chromatic distances between a 48-dot adaptor and the test. Observers with superior discrimination (JND < 2.5{degrees}) showed robust chromatic tuning, adaptation declining as the test moved away from the adaptor hue, whereas poorer discriminators showed none. Using an interindividual-covariance / factor-analytic approach, we found that adaptation strengths at neighboring chromatic distances were highly correlated and fell off with chromatic separation. Principal component analysis extracted two factors, one loading on the larger chromatic distances and one on the smaller; under oblique (promax) rotation the two factors were substantially correlated (r = .66), implying at least two dissociable but overlapping chromatically tuned mechanisms. These results suggest that numerosity adaptation is mediated by multiple, comparatively narrow chromatic channels, resembling the higher-order color mechanisms inferred from color scaling, SSVEP, and fMRI, rather than the two early cardinal axes (L-M, S-(L+M)).