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Vestibular motion perception declines with age, increasing the risk of falling substantially. We performed a two-week perceptual learning intervention using a self-motion direction discrimination task (2800 training trials per person) on a 6 degrees of freedom motion platform in healthy older adults (n = 40, aged 70-88 yr). Linear inter-aural and angular roll tilt vestibular thresholds improved with training (95% credible interval for pre/post difference), suggesting altered sensitivity post-training. Moreover, improved perceptual abilities transfer to actual posture (reduced sway) and gait parameters. Passive self-motion discrimination training provides a new and promising way to counteract age-related sensory decline. It can reduce the risk of falling, and thereby maintain individual autonomy and quality of life.

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Intercepting moving targets is a fundamental skill in human behavior, influencing various domains such as sports, gaming, and other activities. In these contexts, precise visual processing and motor control are crucial for adapting and navigating effectively. Nevertheless, there are still some gaps in our understanding of how these elements interact while intercepting a moving target. This study explored the dynamic interplay among eye movements, pupil size, and interceptive hand movements, with visual and motion uncertainty factors. We developed a simple visuomotor task in which participants used a joystick to interact with a computer-controlled dot that moved along two-dimensional trajectories. This virtual system provided the flexibility to manipulate the target's speed and directional uncertainty during chase trials. We then conducted a geometric analysis based on optimal angles for each behavior, enabling us to distinguish between simple tracking and predictive trajectories that anticipate future positions of the moving target. Our results revealed the adoption of a strong interception strategy as participants approached the target. Notably, the onset and amount of optimal interception strategy depended on task parameters, such as the target's speed and frequency of directional changes. Furthermore, eye-tracking data showed that participants continually adjusted their gaze speed and position, continuously adapting to the target's movements. Finally, in successful trials, pupillary responses predicted the amount of optimal interception strategy while exhibiting an inverse relationship in trials without collisions. These findings reveal key interactions among visuomotor parameters that are crucial for solving complex interception tasks.

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Motion-onset visual evoked potentials (MO VEPs) are robust to dioptric blur when low contrast and low spatial frequency patterns are used for stimulation. To reveal mechanisms of MO VEPs robustness, we studied whether the resistance to defocus persists even when using a high-contrast checkerboard using digital defocus in the emmetropic eyes of 13 subjects (males 20-60 years). We compared the dominant components of MO VEPs to pattern-reversal VEPs (PR VEP), which are sensitive to the blur. For stimulation, we used checkerboard patterns with 15´ and 60´ checks. To defocus the checkerboard, we rendered it with a second-order Zernike polynomial ( Z 2 0 ) with an equivalent defocus of 0, 2, or 4 D. For PR VEP, the checkerboards were reversed in terms of their contrast. To evoke MO VEP, the checkerboard of 60´ checks moved for 200 ms with a speed of 5 or 10 deg/s in the cardinal directions. The MO VEP did not change in peak time (P ≥ 0.0747) or interpeak amplitude (P > 0.0772) with digital blur. In contrast, for PR VEP, the results showed a decrease in interpeak amplitude (P ≤ 6.65ˑ10-4) and an increase in peak time (P ≤ 0.0385). Thus, we demonstrated that MO VEPs evoked by checkerboard, structure containing high spatial content, can be robust to defocus.

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It has been demonstrated that observers can accurately estimate their self-motion direction (i.e., heading) from optic flow, which can be affected by attention. However, it remains unclear how attention affects the serial dependence in the estimation. In the current study, participants conducted two experiments. The results showed that the estimation accuracy decreased when attentional resources allocated to the heading estimation task were reduced. Additionally, the estimates of currently presented headings were biased toward the headings of previously seen headings, showing serial dependence. Especially, this effect decreased (increased) when the attentional resources allocated to the previously (currently) seen headings were reduced. Furthermore, importantly, we developed a Bayesian inference model, which incorporated attention-modulated likelihoods and qualitatively predicted changes in the estimation accuracy and serial dependence. In summary, the current study shows that attention affects the serial dependence in heading estimation from optic flow and reveals the Bayesian computational mechanism behind the heading estimation.

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BACKGROUND: Autism spectrum disorder (ASD), a neurodevelopmental disorder defined by social communication deficits plus repetitive behaviors and restricted interests, currently affects 1/36 children in the general population. Recent advances in functional brain imaging show promise to provide useful biomarkers of ASD diagnostic likelihood, behavioral trait severity, and even response to therapeutic intervention. However, current gold-standard neuroimaging methods (e.g., functional magnetic resonance imaging, fMRI) are limited in naturalistic studies of brain function underlying ASD-associated behaviors due to the constrained imaging environment. Compared to fMRI, high-density diffuse optical tomography (HD-DOT), a non-invasive and minimally constraining optical neuroimaging modality, can overcome these limitations. Herein, we aimed to establish HD-DOT to evaluate brain function in autistic and non-autistic school-age children as they performed a biological motion perception task previously shown to yield results related to both ASD diagnosis and behavioral traits. METHODS: We used HD-DOT to image brain function in 46 ASD school-age participants and 49 non-autistic individuals (NAI) as they viewed dynamic point-light displays of coherent biological and scrambled motion. We assessed group-level cortical brain function with statistical parametric mapping. Additionally, we tested for brain-behavior associations with dimensional metrics of autism traits, as measured with the Social Responsiveness Scale-2, with hierarchical regression models. RESULTS: We found that NAI participants presented stronger brain activity contrast (coherent > scrambled) than ASD children in cortical regions related to visual, motor, and social processing. Additionally, regression models revealed multiple cortical regions in autistic participants where brain function is significantly associated with dimensional measures of ASD traits. LIMITATIONS: Optical imaging methods are limited in depth sensitivity and so cannot measure brain activity within deep subcortical regions. However, the field of view of this HD-DOT system includes multiple brain regions previously implicated in both task-based and task-free studies on autism. CONCLUSIONS: This study demonstrates that HD-DOT is sensitive to brain function that both differentiates between NAI and ASD groups and correlates with dimensional measures of ASD traits. These findings establish HD-DOT as an effective tool for investigating brain function in autistic and non-autistic children. Moreover, this study established neural correlates related to biological motion perception and its association with dimensional measures of ASD traits.

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Motion can produce large changes in the apparent locations of briefly flashed tests presented on or near the motion. These motion-induced position shifts may have a variety of sources. They may be due to a frame effect where the moving pattern provides a frame of reference for the locations of events within it. The motion of the background may act through high-level mechanisms that track its explicit contours or the motion may act on position through the signals from low-level motion detectors. Here we isolate the contribution of low-level motion by eliminating explicit contours and trackable features. In this case, motion still supports a robust shift in probe locations with the shift being in the direction of the motion that follows the probe. Although robust, the magnitude of the shift in our first experiment is about 20% of the shift seen in a previous study with explicit frames and, in the second, about 45% of that found with explicit frames. Clearly, low-level motion alone can produce position shifts although the magnitude is much reduced compared to that seen when high-level mechanisms can contribute.

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Attention and crossmodal interactions are closely linked through a complex interplay at different stages of sensory processing. Within the context of motion perception, previous research revealed that attentional demands alter audiovisual interactions in the temporal domain. In the present study, we aimed to understand the neurophysiological correlates of these attentional modulations. We utilized an audiovisual motion paradigm that elicits auditory time interval effects on perceived visual speed. The audiovisual interactions in the temporal domain were quantified by changes in perceived visual speed across different auditory time intervals. We manipulated attentional demands in the visual field by having a secondary task on a stationary object (i.e., single- vs. dual-task conditions). When the attentional demands were high (i.e., dual-task condition), there was a significant decrease in the effects of auditory time interval on perceived visual speed, suggesting a reduction in audiovisual interactions. Moreover, we found significant differences in both early and late neural activities elicited by visual stimuli across task conditions (single vs. dual), reflecting an overall increase in attentional demands in the visual field. Consistent with the changes in perceived visual speed, the audiovisual interactions in neural signals declined in the late positive component range. Compared with the findings from previous studies using different paradigms, our findings support the view that attentional modulations of crossmodal interactions are not unitary and depend on task-specific components. They also have important implications for motion processing and speed estimation in daily life situations where sensory relevance and attentional demands constantly change.

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Recently, there has been a resurgence in experimental and conceptual efforts to understand how brain rhythms can serve to organize visual information. Oscillations can provide temporal structure for neuronal processing and form a basis for integrating information across brain areas. Here, we use a bistable paradigm and a data-driven approach to test the hypothesis that oscillatory modulations associate with the integration or segregation of visual elements. Spectral signatures of perception of bound and unbound configurations of visual moving stimuli were studied using magnetoencephalography (MEG) in ambiguous and unambiguous conditions. Using a 2 × 2 design, we were able to isolate correlates from visual integration, either perceptual or stimulus-driven, from attentional and ambiguity-related activity. Two frequency bands were found to be modulated by visual integration: an alpha/beta frequency and a higher frequency gamma-band. Alpha/beta power was increased in several early visual cortical and dorsal visual areas during visual integration, while gamma-band power was surprisingly increased in the extrastriate visual cortex during segregation. This points to an integrative role for alpha/beta activity, likely from top-down signals maintaining a single visual representation. On the other hand, when more representations have to be processed in parallel gamma-band activity is increased, which is at odds with the notion that gamma oscillations are related to perceptual coherence. These modulations were confirmed in intracranial EEG recordings and partially originate from distinct brain areas. Our MEG and stereo-EEG data confirms predictions of binding mechanisms depending on low-frequency activity for long-range integration and for organizing visual processing while refuting a straightforward correlation between gamma-activity and perceptual binding. PRACTITIONER POINTS: Distinct neurophysiological signals underlie competing bistable percepts. Increased alpha/beta activity correlate with visual integration while gamma correlates with segmentation. Ambiguous percepts drive alpha/beta activity in the posterior cingulate cortex.

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The ability to use past learned experiences to guide decisions is an important component of adaptive behavior, especially when decision-making is performed under time pressure or when perceptual information is unreliable. Previous studies using visual discrimination tasks have shown that this prior-informed decision-making ability is impaired in Parkinson's disease (PD), but the mechanisms underlying this deficit and the precise impact of dopaminergic denervation within cortico-basal circuits remain unclear. To shed light on this problem, we evaluated prior-informed decision-making under various conditions of perceptual uncertainty in a sample of 13 clinically established early PD patients, and compared behavioral performance with healthy control (HC) subjects matched in age, sex and education. PD patients and HC subjects performed a random dot motion task in which they had to decide the net direction (leftward vs. rightward) of a field of moving dots and communicate their choices through manual button presses. We manipulated prior knowledge by modulating the probability of occurrence of leftward vs. rightward motion stimuli between blocks of trials, and by explicitly giving these probabilities to subjects at the beginning of each block. We further manipulated stimulus discriminability by varying the proportion of dots moving coherently in the signal direction and speed-accuracy instructions. PD patients used choice probabilities to guide perceptual decisions in both speed and accuracy conditions, and their performance did not significantly differ from that of HC subjects. An additional analysis of the data with the diffusion decision model confirmed this conclusion. These results suggest that the impaired use of priors during visual discrimination observed at more advanced stages of PD is independent of dopaminergic denervation, though additional studies with larger sample sizes are needed to more firmly establish this conclusion.

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Some locomotor tasks involve steering at high speeds through multiple waypoints within cluttered environments. Although in principle actors could treat each individual waypoint in isolation, skillful performance would seem to require them to adapt their trajectory to the most immediate waypoint in anticipation of subsequent waypoints. To date, there have been few studies of such behavior, and the evidence that does exist is inconclusive about whether steering is affected by multiple future waypoints. The present study was designed to address the need for a clearer understanding of how humans adapt their steering movements in anticipation of future goals. Subjects performed a simulated drone flying task in a forest-like virtual environment that was presented on a monitor while their eye movements were tracked. They were instructed to steer through a series of gates while the distance at which gates first became visible (i.e., lookahead distance) was manipulated between trials. When gates became visible at least 1-1/2 segments in advance, subjects successfully flew through a high percentage of gates, rarely collided with obstacles, and maintained a consistent speed. They also approached the most immediate gate in a way that depended on the angular position of the subsequent gate. However, when the lookahead distance was less than 1-1/2 segments, subjects followed longer paths and flew at slower, more variable speeds. The findings demonstrate that the control of steering through multiple waypoints does indeed depend on information from beyond the most immediate waypoint. Discussion focuses on the possible control strategies for steering through multiple waypoints.

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We investigated whether adaptation from implied motion (IM) is transferred to real motion using optokinetic nystagmus (OKN) in infants. Specifically, we examined whether viewing a series of images depicting motion shifted infants' OKN responses to the opposite direction of random dot kinematograms (RDKs). Each RDK was presented 10 times in a pre-test, followed by 10 trials of IM adaptation and test. During the pre-test, the signal dots of the RDK moved left or right. During IM adaptation, 10 randomly selected images depicting leftward (or rightward) IM were presented. In the test, the RDK was presented immediately after the last IM image. An observer, blinded to the motion direction, assessed the OKN direction. The number of matches in OKN responses for each RDK direction was calculated as the match ratio of OKN. We conducted a two-way mixed analysis of variance, with age group (5-6 months and 7-8 months) as the between-participant factor and adaptation (pre-test and test) as the within-participant factor. Only in 7-8 months the OKN responses were shifted in the opposite direction of RDK by viewing a series of images depicting motion, and these infants could detect both IM and RDK motion directions in the pre-test. Our results indicate that detecting the IM and RDK directions might induce direction-selective adaptation in 7-8 months.

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Significant progress has been achieved in multi-object tracking (MOT) through the evolution of detection and re-identification (ReID) techniques. Despite these advancements, accurately tracking objects in scenarios with homogeneous appearance and heterogeneous motion remains a challenge. This challenge arises from two main factors: the insufficient discriminability of ReID features and the predominant utilization of linear motion models in MOT. In this context, we introduce a novel motion-based tracker, MotionTrack, centered around a learnable motion predictor that relies solely on object trajectory information. This predictor comprehensively integrates two levels of granularity in motion features to enhance the modeling of temporal dynamics and facilitate precise future motion prediction for individual objects. Specifically, the proposed approach adopts a self-attention mechanism to capture token-level information and a Dynamic MLP layer to model channel-level features. MotionTrack is a simple, online tracking approach. Our experimental results demonstrate that MotionTrack yields state-of-the-art performance on datasets such as Dancetrack and SportsMOT, characterized by highly complex object motion.

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Self-supervised contrastive learning draws on power representational models to acquire generic semantic features from unlabeled data, and the key to training such models lies in how accurately to track motion features. Previous video contrastive learning methods have extensively used spatially or temporally augmentation as similar instances, resulting in models that are more likely to learn static backgrounds than motion features. To alleviate the background shortcuts, in this paper, we propose a cross-view motion consistent (CVMC) self-supervised video inter-intra contrastive model to focus on the learning of local details and long-term temporal relationships. Specifically, we first extract the dynamic features of consecutive video snippets and then align these features based on multi-view motion consistency. Meanwhile, we compare the optimized dynamic features for instance comparison of different videos and local spatial fine-grained with temporal order in the same video, respectively. Ultimately, the joint optimization of spatio-temporal alignment and motion discrimination effectively fills the challenges of the missing components of instance recognition, spatial compactness, and temporal perception in self-supervised learning. Experimental results show that our proposed self-supervised model can effectively learn visual representation information and achieve highly competitive performance compared to other state-of-the-art methods in both action recognition and video retrieval tasks.

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Human facial features (eyes, nose, and mouth) allow us to communicate with others. Observing faces triggers physiological responses, including pupil dilation. Still, the relative influence of social and motion content of a visual stimulus on pupillary reactivity has never been elucidated. A total of 30 adults aged 18-33 years old were recorded with an eye tracker. We analysed the event-related pupil dilation in response to stimuli distributed along a gradient of social salience (non-social to social, going from objects to avatars to real faces) and dynamism (static to micro- to macro-motion). Pupil dilation was larger in response to social (faces and avatars) compared to non-social stimuli (objects), with surprisingly a larger response for avatars. Pupil dilation was also larger in response to macro-motion compared to static. After quantifying each stimulus' real quantity of motion, we found that the higher the quantity of motion, the larger the pupil dilated. However, the slope of this relationship was not higher for social stimuli. Overall, pupil dilation was more sensitive to the real quantity of motion than to the social component of motion, highlighting the relevance of ecological stimulations. Physiological response to faces results from specific contributions of both motion and social processing.

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BACKGROUND: The perception of biological motion requires accurate prediction of the spatiotemporal dynamics of human movement. Research on Developmental Coordination Disorder (DCD) suggests deficits in accurate motor prediction, raising the question whether not just action execution, but also action perception is perturbed in this disorder. AIMS: To examine action perception by comparing the neural response to the observation of apparent biological motion in children with and without DCD. METHODS AND PROCEDURES: Thirty-three participants with and 33 without DCD, matched based on age (13.0 ± 2.0), sex and writing hand, observed sequences of static body postures that showed either fluent or non-fluent motion, in which only the fluent condition depicted apparent biological motion. Using a recently validated paradigm combining EEG frequency tagging and apparent biological motion (Cracco et al., 2023), the perception of biological motion was contrasted with the perception of individual body postures. OUTCOMES AND CONCLUSIONS: Children with DCD did not show reduced sensitivity to apparent biological motion compared with typically developing children. However, the DCD group did show a reduced brain response to repetitive visual stimuli, suggesting altered predictive processing in the perceptual domain in this group. Suggestions for further research on biological motion perception in DCD are identified.

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BACKGROUND: To better personalize treatment and monitor recovery of individuals with low back pain, objective tests of sensorimotor functions, such as lumbar proprioception, must be selected based on their reliability and validity. The primary objective of this study was to test the concurrent validity of three measures of lumbar proprioception. METHODS: Thirty-one participants performed three lumbar proprioception tests (motion perception threshold, active and passive joint positioning sense), a whole-body mobility and balance (time up-and-go) and two trunk-specific postural control (threshold of stability and sensor-based sway measures) tests. RESULTS: Only the motion perception threshold proprioception test showed some validity, correlating with the trunk-specific postural control tests [r range (positive values): 0.37 to 0.60]. The three lumbar proprioception measures were not correlated to each other. The threshold of stability measure was correlated with the time up-and-go (r = 0.37) and trunk-specific (sensor-based sway measures) postural control [r range (positive values): 0.48 to 0.77] tests. CONCLUSION: The present study generated three original findings. Only the motion perception threshold proprioception test demonstrated its concurrent validity. In fact, the three lumbar proprioception tests performed in the present study were not correlated to each other, thus assessing different constructs. Finally, the threshold of stability protocol was validated against other tests. These findings will help in selecting the most appropriate lumbar proprioception measures to study the effects of exercise treatments in patients with back pain.

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For successful interactions with the world, we often have to evaluate our own performance. Although eye movements are one of the most frequent actions we perform, we are typically unaware of them. Here, we investigated whether there is any evidence for metacognitive sensitivity for the accuracy of eye movements. Participants tracked a dot cloud as it followed an unpredictable sinusoidal trajectory and then reported if they thought their performance was better or worse than their average tracking performance. Our results show above-chance identification of better tracking behavior across all trials and also for repeated attempts of the same target trajectories. Sensitivity in discriminating performance between better and worse trials was stable across sessions, but judgements within a trial relied more on performance in the final seconds. This behavior matched previous reports when judging the quality of hand movements, although overall metacognitive sensitivity for eye movements was significantly lower.

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In this paper, we show that the model we proposed earlier to account for the disparity vergence eye movements (disparity vergence responses, or DVRs) in response to horizontal and vertical disparity steps of white noise visual stimuli also provides an excellent description of the short-latency ocular following responses (OFRs) to broadband stimuli in the visual motion domain. In addition, we reanalyzed the data and applied the model to several earlier studies that used sine-wave gratings (single or a combination of two or three gratings) and white noise stimuli. The model provides a very good account of all of these data. The model postulates that the short-latency eye movements-OFRs and DVRs-can be accounted for by the operation of two factors: an excitatory drive, determined by a weighted sum of contributions of stimulus Fourier components, scaled by a global contrast normalization mechanism. The output of the operation of these two factors is then nonlinearly scaled by the total contrast of the stimulus. Despite different roles of disparity (horizontal and vertical) and motion signals in visual scene analyses, the earliest processing stages of these different signals appear to be very similar.

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