Vision Research

Zebrafish (Danio rerio) are an important vertebrate model for vision and neuroscience research. In the larval stages, the aquatic species begins to elicit the optomotor response (OMR) to stabilize themselves in water -- a behaviour that may be exploited in the laboratory to measure visual acuity. However, up to now, the measurement of the OMR in juvenile and adult zebrafish has been limited due to their behavioural complexity. Here, we optimize a protocol to assay zebrafish aged between 4 and 9 weeks-post-fertilization, by displaying sinusoidal gratings parallel to the zebrafish eye to elicit a robust OMR. We assessed the visual spatial-frequency tuning function of an environmentally induced myopia model to confirm the sensitivity and robustness of the protocol. Additionally, we show the OMR is sensitive to the contrast and temporal resolution of the sinusoidal gratings. Furthermore, we found that the time between stimulus presentations impact the spatial-frequency tuning function likely as time is required for zebrafish to return to baseline swimming after eliciting the OMR. Finally, we found that the OMR after ten versus twenty seconds of stimulus onset appears comparable; indicating that robust OMR responses in zebrafish can be elicited through relatively short stimulus presentations. Through the experiments conducted, we present an optimized protocol specific to zebrafish. The protocol may be used to follow the progression or treatment efficacy of progressive neurological disorders including specific visual disorders and higher brain functions with visual endophenotypes. Ultimately, this protocol allows for high-throughput robust measures of visual and neural function in zebrafish.

Mental rotation in 3D is a key cognitive skill involving dynamic spatial transformations, for which pronounced individual differences have been documented. Here we ask whether individual differences in 3D abilities can be explained by analogous differences in 2D abilities. 3D mental-rotation was assessed by the Vandenberg & Kruse Mental Rotation Test (3D-MRT) and examined for association with performance and underlying electrocortical mechanisms during a 2D letter rotation task. Participants (N=40) first completed the MRT and then performed a computerized 2-D letter rotation task in which they had to identify whether letters were oriented in a standard or a mirrored direction (parity judgment) when rotated at 0{degrees}, 60{degrees}, 120{degrees}, and 180{degrees} while EEG was recorded. Reaction times (RTs) and error rates increased with angular disparity. The angular disparity effect on RT was smaller for mirrored letters. Low, relative to high, 3D-MRT scoring participants showed more pronounced accuracy declines at higher rotation angles. An EEG Event Related Potential (ERP) known as the Rotation-Related Negativity (RRN) became more pronounced with increasing angular disparity. High 3D-MRT scores were associated with a stronger RRN response at central-parietal sites. In addition, the ERP-P3b wave was more pronounced at central-parietal sites for low 3D-MRT scorers, independent of angular disparity. It is concluded that 3D rotational ability is positively associated with 2D mental rotation performance, and more strongly with enhanced recruitment of neural visual-spatial cortical representations than with enhanced recruitment of more general cognitive resources.

Saccades made during memory maintenance prioritize memory for the saccade target, but it is unclear if this benefit is specific to a location or extends across memorized objects. In three experiments, we examined whether saccadic selection spreads to other locations within the same object. In Experiment 1, we asked observers to remember three oriented Gabors presented either within contour-defined objects or without object structure. A subsequent movement cue prompted observers to move their eyes to the indicated location. We then probed memory for stimuli at locations equidistant from the saccade target, in either the same or a different object. Memory was best for stimuli at locations congruent with the saccade target, and consistently weaker for other stimuli presented in the same or a different object than the saccade target. In Experiment 2, we created more complex objects by adding more object features to the stimulus. Again, memory performance was best for stimuli congruent with the saccade target location, whereas memory in incongruent trials was worse and similar for stimuli in the same and different object as the saccade target. In Experiment 3, we tested if saccadic selection is present and propagates within the object in a change detection task. Again, memory performance (i.e., change detection) was best at the saccade target location. However, this memory benefit also spread to other locations within the same object. Our results imply that saccadic selection in visual working memory is primarily space-based but can also spread towards locations within the object where a saccade was directed.

In previous studies by the author on binocular vision with the asymmetric eye (AE), which models a healthy human eye with misaligned optical components, the results were primarily presented in the Rodrigues vector (RV) framework and supported by simulations and 3D visualizations in GeoGebras dynamic geometry environment. In this paper, the novel geometric kinematics of the human eye, that is, the eye with misaligned optics, and simplified assumptions about the eye rotations (the eyes translational movements are disregarded), are developed within the framework of rigid-body rotations. The originality of the analysis lies in a precise geometric decomposition of a full rotation of the eyes posture into a torsion-free rotation (the geodesic part) and a torsional rotation (the non-geodesic extension of the geodesic part). This decomposition is extended to the corresponding decomposition of the angular velocity. A novel derivation of the eyes angular velocity from the RV formulation of the eye kinematics is proposed.

Homeostatic plasticity of intrinsic excitability (IE) in the visual system has been essentially shown at the cortical level but whether thalamic nuclei also express homeostatic plasticity of IE is unknown. We show here that 4 days of monocular deprivation (MD) at eye opening induces a homeostatic change in IE in dorsal lateral geniculate nucleus (dLGN) neurons. Neurons recorded in the dLGN region activated by the deprived eye are more excitable than neurons recorded in the dLGN region activated by the open eye. No significant changes were observed following 7 days of MD, however. Enhanced excitability in neurons from the deprived side after 4 days of MD was associated with a reduced Kv1-dependent LTP-IE, a smaller voltage ramp, and a reduced inter-spike interval, suggesting that Kv1 channels are down-regulated in deprived dLGN neurons. Furthermore, the ankyrin G signal of the axon initial segment was larger in deprived dLGN neurons compared with open ones, indicating that Nav1 channel number also undergoes homeostatic regulation, and Kv1.1 channel signals were lower in deprived neurons compared to open ones. In addition, electrical coupling was found to be strengthened in neurons displaying enhanced IE following either brief (4 days) or long (10 days) MD. These results suggest that homeostatic and Hebbian plasticity in the dLGN share common expression mechanisms involving the regulation of Kv1 channels, Nav1 channels and electrical coupling between relay neurons.

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.

PurposeAlthough electroretinography (ERG) is vital for evaluating retinal function, conventional corneal electrodes slide or detach in animals. This study aimed to investigate the effectiveness of a novel approach to ERG recording using a metal eyelid speculum for both active and reference electrodes in conjunction with a skin electrode-based ERG device. MethodsWe tested a stainless-steel eyelid speculum as both active and reference electrodes with a skin-electrode ERG system (HE-2000vet) in six healthy Japanese White rabbits. Dark-adapted rod and maximal responses and light-adapted cone and 30 Hz flicker ERGs were recorded in three weekly sessions. ResultsReproducible waveforms with identifiable a- and b-waves were obtained in every eye; rod b-waves reached 50-90 {micro}V and cone b-waves 40-55 {micro}V. Intraclass correlation coefficients revealed substantial interocular agreement and moderate-to-substantial inter-session reproducibility for b-wave amplitude and implicit time, whereas a-wave metrics were less reliable owing to lower amplitudes. The advantages of speculum electrode over corneal electrodes are that it requires no fur shaving, maintains stable contact regardless of globe orientation, and allows real-time observation. ConclusionsThis study demonstrated that an eyelid-speculum electrode is a practical, non-invasive alternative for veterinary and experimental ERG recordings, producing signal quality sufficient for longitudinal and interocular analyses while avoiding cosmetic and technical drawbacks of conventional methods.

Visual response strength in the primate superior colliculus (SC) has recently been shown to inversely correlate with trial-by-trial saccadic reaction time in a much stronger way than visual response strength in the primary visual cortex (V1). However, for any given visual stimulus onset, populations of neurons in each brain area are concurrently activated, leaving open the question of how V1 visual response strength can predict trial-by-trial saccadic reaction time when multiple simultaneously recorded neurons are taken into account. Using a classic visually-guided saccade task, here we assessed the quality of predicting trial-by-trial saccadic reaction time from the visual response strengths of 1 to 10 simultaneously recorded neurons in each brain area. For each session, we modeled saccadic reaction time as a weighted linear combination of the visual response strengths of N simultaneously recorded neurons. Consistent with the prior work, the visual response strength of a single SC neuron was better than that of a single V1 neuron at predicting reaction time. By adding more simultaneously recorded neurons, the prediction got much better in the SC, but not in V1.Only for 100% contrast dark stimuli (darker in luminance than the surrounding gray background) did V1 show an increase in prediction quality with more simultaneously recorded neurons. This increase, which was still substantially weaker than in the SC, could reflect the preference of V1 neurons for dark contrasts. These results suggest that despite qualitative similarities between SC and V1 visual responses, SC visual responses are functionally reformatted from their V1 counterparts. SignificanceThe superior colliculus (SC) is an important sensory-motor structure for controlling eye movements, and it receives a significant portion of its inputs directly from the primary visual cortex (V1). Despite this, SC visual responses are much better correlated with trial-by-trial variability in saccadic eye movement timing than V1 visual responses, and this effect is strongly amplified when considering simultaneously recorded neurons. Thus, SC and V1 visual responses serve fundamentally different functions from a motor perspective.

BackgroundThe relevance of spontaneous activity has been unlocked thanks to recent large scale recordings that revealed, via Shared Variance Component Analysis (SVCA), the high-dimensional nature of the ongoing activity. A fundamental problem is how the dimension modifies when more neurons are included in the analysis. Contradictory results have been reported on this subject based on SVCA and Principal Component Analysis (PCA). New MethodWe investigate pro et contra of SVCA and PCA for the identification of reliable responses encoding underlying state variables. We focus on common features of the spectra of the reliable variances (RVs) and on their dimensionality. The analysis is demonstrated on previously published Ca2+ data from the visual and the dorsal cortex in head fixed mice during spontaneous behavior. ResultsRVs grow proportionally to the number N of neurons and show a power-law decay k- with the k-th SVC dimension over a range bounded by a maximal dimension kc, initially diverging as N 1/ and then saturating at sufficiently large N. The reliable dimensionality, estimated with different methodologies, also shows a clear saturation to an asymptotic value for large N. Furthermore, its value decreases when becomes larger, as demonstrated by employing experimental data as well as theoretical predictions. ConclusionWe have shown that SVCA is an extremely effective tool to extract reliable features from the neural signals, and that the exponent represents a biomarker able to reveal the level of correlation of the neurons as well as the dimensionality of the reliable space. HighlightsO_LIAdvantages and drawbacks of Shared Variance Component Analysis to extract reliable signals from neural data C_LIO_LIComparison of different methods to estimate reliable neural dimensionality associated to spontaneous activity C_LIO_LIAnalytical expressions of embedding dimensionality for power-law decaying reliable variances C_LIO_LIBounded growth of the dimensionality with the number of neurons C_LI

The present study examined whether thematic reversal anomalies are processed similarly across subject and object experiencer constructions in Malayalam. Event-related brain potentials (ERPs) were recorded as 30 first-language speakers of Malayalam read transitive sentences with the two types of experiencer verbs, in which the thematic role assignment for the preceding arguments was either correct or reverse. The reversal anomaly became apparent only at the position of the experiencer verb. A linear mixed-models analysis confirmed a biphasic N400-P600 effect at the verb for both verb types when the argument roles were reverse. Thus, our results suggest a uniform processing strategy for TRAs irrespective of the type of experiencer verb involved. However, the N400 amplitude was larger for the object experiencer verb compared to subject experiencer verbs. We suggest that the quantitative difference observed for object experiencer verbs is due to the inverse linking of grammatical function and thematic roles associated with these verbs. In other words, verb-specific linking properties modulate the processing of TRAs involving object experiencer verbs. We argue that this modulation occurs because the parser recalibrates cue weighting when the expected form-to-meaning mappings are overridden by the inverse linking properties of object experiencer verbs.

Habitat modification is a major driver of avian population change in tropical savanna ecosystems. This study investigated habitat-related variation in the abundance of the Red-cheeked Cordon-bleu (Uraeginthus bengalus) across human settlements and surrounding farmlands in Laminga Village, Jos-East Local Government Area, Plateau State, Nigeria. Field surveys were conducted over a three-week period in November 2024 using 21 line transects sampled during peak bird activity periods. Bird abundance data were analysed using a Poisson Generalized Linear Model (GLM). Results showed that habitat type significantly influenced abundance, with significantly lower abundance recorded in human settlements compared to farmlands ({beta} = -0.836, SE = 0.192, z = -4.359, p < 0.001). Transect length positively influenced abundance ({beta} = 0.028, SE = 0.008, z = 3.600, p < 0.001). Model performance improved substantially from the null deviance (159.88) to the residual deviance (125.85), with an Akaike Information Criterion (AIC) value of 306.32. The findings suggest that farmlands provide more favourable habitat conditions for the species, likely due to greater vegetation availability and reduced structural disturbance relative to settlement areas. The study highlights the ecological importance of low-intensity agricultural landscapes in supporting avian persistence within human-modified savanna environments.

Understanding how anthropogenic disturbance and vegetation structure influence bird abundance is important for biodiversity conservation in rapidly changing tropical landscapes. This study evaluated the effects of anthropogenic and vegetation-related variables on the abundance of the Red-cheeked Cordon-bleu (Uraeginthus bengalus) in human settlements and surrounding farmlands in Laminga Village, Jos-East Local Government Area, Plateau State, Nigeria. Bird surveys were conducted using line transects and quadrat-based vegetation assessments during November 2024. Poisson Generalized Linear Models (GLMs) were used to examine the influence of anthropogenic and vegetation predictors on abundance. Among anthropogenic variables, building density significantly reduced abundance ({beta} = -0.141, SE = 0.060, z = -2.333, p = 0.020), whereas human presence ({beta} = -0.073, p = 0.141) and noise level ({beta} = 0.009, p = 0.592) did not significantly influence abundance. Average grass height showed a marginal positive relationship with abundance ({beta} = 2.008, SE = 1.051, z = 1.910, p = 0.056), while hedgerow presence, hedgerow height, grass cover, and bare ground cover were not significant predictors. The vegetation model produced the lowest residual deviance (91.19) and AIC value (297.66), indicating comparatively stronger explanatory performance. The results suggest that structural habitat characteristics and building density may play more important roles in shaping Red-cheeked Cordon-bleu abundance than human activity or noise levels alone. These findings provide insight into species responses to environmental disturbance in human-modified savanna ecosystems.

Learning to read requires linking auditory and visual information, yet how the developing brain maps information across sensory modalities remains poorly understood. To shed light on this topic we employed functional MRI to investigate hemodynamic brain responses during spoken and written word or pseudoword recognition in 61 primary school children with different levels of reading experience. Audiovisual representational similarity of activation patterns in the inferior frontal gyrus, inferior parietal lobule, superior temporal gyrus, and temporo-occipital cortex, increased linearly with school grade and this effect was largest in the left posterior superior temporal gyrus. Our results suggest that learning to read is related to a progressively increasing similarity of auditory and visual word representations within canonical language areas.

Ovarian cancer is one of the gynecological cancer types, which, if metastasized and not detected early, can cause deaths among women. Therefore, there is a need to accurately predict drug responses to ovarian cancer. A gynecological pathologist inspects abnormality in tissues, followed by providing a report about patients; however, such a diagnostic process is (1) hard; (2) requires experience; and (3) time consuming. Moreover, existing tools are far from perfect. Hence, we present a computational pipeline to improve predicting drug response pertaining to ovarian cancer, derived as follows. First, we download digital pathology images pertaining to ovarian bevacizumab response from the cancer imaging archive repository. We employed histogram of oriented gradients to images, constructing feature vectors, provided to Fisher linear discriminant analysis to change the representation through dimensionality reduction. Then, we provide reduced-dimensionality data for regression analysis through support vector regression coupled with various kernels and calculating the area under the ROC curve (AUC). Experimental results against transformer-based models (ViT and Swin) and other deep learning (DL) models (VGG16, ResNet50, InceptionV3, MobileNetV2, and EfficientNetB6) demonstrate that our approach with radial kernel (named SVRD+R) yielded an AUC performance improvements of 17% against the best-performing transformer-based model (ViT) while obtaining an AUC performance improvements of 14.9% when compared against the best DL-based model (MobileNetV2). These results demonstrate the superiority and feasibility of our AI-based pipeline when tackling prediction problems pertaining to gynecologic cancer studies. MSC92B05; 68T09

Background: The Colour Blind Quality of Life Scale (CBQoL) is a questionnaire developed to assess the quality of life of individuals with congenital colour vision deficiency (CVD). This study aimed to translate the English version of the CBQoL into Vietnamese and evaluate the validity and reliability of the Vietnamese version (CBQoL-VN). Methods: A forward-backward translation method was performed to produce the Vietnamese text. Content validity was assessed by six experts in vision care. Reliability testing involved 30 participants with congenital CVD, while discriminant validity was evaluated by comparing this group against 30 participants with normal colour vision. Results: Following expert consensus, two items were removed and one transportation-related item was added. The content validation index (CVI) values of 1.0 for relevance, clarity, and understandability indicated excellent content validity. Internal consistency was high, with a Cronbach's alpha of 0.95 for the full scale. Discriminant validity analysis showed that participants with congenital CVD scored significantly lower across all CBQoL-VN domains compared to those with normal colour vision. Conclusions: The modified CBQoL-VN is a valid and reliable instrument for assessing the quality of life of individuals with congenital CVD in the Vietnamese population.

Perceptual systems in humans and many other animals are able to segment scenes into regions that are likely to be physically meaningful. This ability depends on having low-level mechanisms that can accurately categorize whether local image patches are samples from the same or different kinds of texture. We find that using spatial proximity as a proxy for same-different ground truth makes it possible to train accurate decision variables and bounds directly from arbitrary natural images with no feedback. We also find that performance can be further improved by using proximity as a ground truth for adjusting the final decision variables and bounds for the current image/scene. These surprising findings result from the simple fact that under a wide range of conditions proximity discrimination (near vs. far) and texture discrimination (same vs. different) have mathematically identical decision bounds if the same image features are used for both tasks. We used the decision variables and bounds trained on natural images as the initial steps in a hierarchical Bayesian observer (HBO) model of texture discrimination [9]. Given the relative simplicity of this HBO model, it did an excellent job of segmenting images having randomly shaped regions containing arbitrary natural textures. We suggest that the proximity proxy is something that natural selection could discover and exploit for any same-different task where the task-relevant stimulus features also vary systematically with distance in space and/or time. For example, natural selection could have created developmental learning/plasticity mechanisms that exploit the proximity proxy.

Purpose Considering that myopia is associated with thinning of the ocular coats, this study investigated the inter-relationship of retinal, choroidal and scleral thickness in foveal regions in Indian high myopes. Methods A total of 23 high myopes (spherical equivalent refraction [&le;]-6.00D) aged 16 to 35 years underwent posterior segment imaging with swept-source optical coherence tomography. The retinal, choroidal and scleral thickness was determined using semi-automated custom-designed software at sub-foveal regions. Axial length was determined using Lenstar LS 900 non-contact biometer. Results The mean plus-or-minus sign SD axial length was 30.17 plus-or-minus sign 2.23 mm, sub-foveal retinal thickness was 245 plus-or-minus sign 28 lower case Greek mum, sub-foveal choroidal thickness was 82 plus-or-minus sign 46 lower case Greek mum, and sub-foveal scleral thickness was 254 plus-or-minus sign 68 lower case Greek mum. The choroid was significantly thinner compared to the retina and sclera (p<0.001). With a 1 mm increase in axial length, there was no significant variation in sub-foveal retinal (increased by 0.86 lower case Greek mum) and scleral thickness (decreased by 4.31 lower case Greek mum, p[&ge;]0.05), but sub-foveal choroidal thickness decreased by 10.35 lower case Greek mum (p=0.02). For a 1D decrease in spherical equivalent refraction, the choroidal thickness reduced significantly (decreased by 5.88 lower case Greek mum, p<0.001), while there was no significant variation in retinal (decreased by 0.68 lower case Greek mum, p=0.55) and scleral thickness (increased by 0.13 mum, p=0.98). The association of the sub-foveal retinal, choroidal, and scleral thickness was weak and was not significant in high myopes (p[&ge;]0.10). Conclusions With increasing axial length and severity of myopia in high myopes, compared to scleral and retinal thickness, the choroidal thickness alone decreased significantly. Our findings indicate that the changes in the choroid do not necessarily reflect the changes in retinal and scleral thickness and highlight the importance of the choroid as a marker for axial elongation even in high myopes.

BackgroundThis study examines a competition-based model (C-model) designed to capture the temporal dynamics of successive brain microstates derived from electroencephalography (EEG) recordings during eyes-open conditions. The analyzed data were obtained from a public repository comprising microstate sequences from 60 sessions of a single subject [1]. When applied to microstate dynamics, the C-model posits a stochastic competition among neural circuits underlying the expression of individual microstates. MethodsThe model is formulated at a conceptual level (computational level in Marrs framework) and employs a geometric distribution to account for the long right tail of microstate duration distributions, interpreted as the probability of "failure" of the currently active microstate to persist. To account for the short-lived left tail, the model incorporates a transient increase in the stability of the currently active network, or equivalently, a temporary decrease in the activation probability of competing microstates (refractory period). ResultsThe model provides a good fit to the microstate duration distributions across all 60 sessions. One third of sessions showed microstate identity sequential dependency with respect to the previous microstates. DiscussionThese results suggest that the C-model captures key aspects of microstate temporal structure. Moreover, because microstate probabilities can be modulated by psychophysiological conditions--including the influence of previously active networks--the model may serve as a building block for more comprehensive neurobiological frameworks of neural and behavioral dynamics. In such frameworks, microstate sequences could emerge from structured competition and flow among neural networks supporting microstate expression.

Past work has indicated that expectation can modulate neural responses to visual stimuli, but it is unclear whether these effects remain consistent across different types of unexpected stimuli. Here, we measured and compared neural prediction effects associated with semantic category and presentation frequency-based expectations in real-world object stimuli. Participants (n = 35) viewed real-world object images in rapid serial visual presentation (RSVP) streams. Semantically unexpected stimuli occurred when a stimulus was presented in a semantically incongruent stream. Low-frequency violations occurred when a rarely presented stimulus was displayed in a semantically congruent stream. Multivariate pattern analysis of electroencephalography (EEG) was used to quantify and compare the degree of information represented in neural activity for stimuli in different prediction conditions. Semantically expected stimuli yielded lower decoding accuracy relative to random (unpredictable) stimuli (125-313 ms post-onset) while semantically unexpected stimuli exhibited increased decoding accuracy (199-238 ms & 523-559 ms). Low-frequency violations yielded decoding accuracy which was not significantly different from semantically expected stimuli. Exploratory analyses indicated that dissimilarity between expected and presented stimuli quantified in terms of higher-level stimulus features, but not low-level visual features, modulated the observed neural prediction effects. These results demonstrate that different types of prediction violations have distinct modulatory effects on neural responses, providing novel insight into the neural implementation of predictive processing.

Musical rhythm is often experienced with a periodic beat, serving as a temporal reference for coordination with the rhythm. Thus far, models of beat processing have mainly relied on representing sensory inputs as patterns of onset timing, with limited consideration of other sensory features. Here, we challenge this view by showing that the internal representation of beat is affected by other temporal features of the stimulus beyond onset timing alone. We recorded electroencephalography (EEG) while participants listened to rhythmic sequences designed to elicit a beat. Across conditions, we manipulated the duration of the tones conveying the rhythms, while keeping all other parameters identical, including overall intensity, speed, and rhythmic pattern structure. Crucially, the beat periodicity was enhanced in neural activity with increased sound duration, even though the beat periodicity was not prominent in the acoustic features, thus ruling out basic sensory confounds. These results demonstrate the preferential role of longer sound durations in fostering temporal scaffolding processes that integrate fast rhythmic inputs into behavior-relevant internal structures such as the beat. More generally, our findings are compatible with a holistic processing account whereby a range of features beyond onset timing may be integrated into a neural representation of rhythm. Graphical Abstract: Fig. 2EEG was recorded while listeners heard rhythmic sequences eliciting a beat. Sound duration (sonic duty cycle) was varied across four conditions while speed, pattern, and intensity stayed constant. Beat-related EEG responses increased with longer sounds, and were enhanced in all conditions compared to auditory nerve model envelopes, which did not show prominent energy at the beat periodicity, ruling out sensory confounds. Results support holistic rhythm processing beyond onset timing alone. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=101 SRC="FIGDIR/small/721298v1_fig2.gif" ALT="Figure 2"> View larger version (27K): org.highwire.dtl.DTLVardef@10a0599org.highwire.dtl.DTLVardef@f5a95forg.highwire.dtl.DTLVardef@42d1ceorg.highwire.dtl.DTLVardef@dc58a7_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 2.C_FLOATNO EEG and auditory nerve model output analysis based on magnitude spectrum and autocorrelation. Each row represents a duty cycle condition. The two columns on the left represent the magnitude spectrum-based analysis. The first column represents the group-level averaged magnitude spectra at a pool of fronto-central electrodes, across conditions. Beat-related frequencies are shown in red, and beat-unrelated frequencies are shown in blue. Scalp topographies of the neural activity measured at the average magnitudes of beat-related (in red circle) and unrelated (in blue circle) frequencies are represented as insets. The second column represents the normalized magnitude spectra obtained from the auditory nerve model output for each duty cycle sequence. The two columns on the right represent the autocorrelation-based analysis (for visualization purposes, only a subset of lags from 0 to 2.4 s corresponding to the pattern duration is shown). The first column represents the group-level averaged autocorrelation function measured from the same pool of fronto-central electrodes, across conditions. Beat-related lags are shown in red, and beat-unrelated lags are shown in blue. The second column represents the autocorrelation function of the auditory nerve model output for each duty cycle sequence. C_FIG