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.

Inspired by the motion processing pathway, this paper proposes a bio-inspired feedforward spiking network model based on Hodgkin-Huxley neurons for human motion perception. The proposed network mimics the mechanisms of direction selectivity found in simple and complex cells of the primary visual cortex. Simple cells\' receptive fields are modeled using Gabor energy filters, while complex cells\' receptive fields are constructed by integrating the responses of simple cells in an energy model. To generate the motion map, the spiking output of the network integrates motion information encoded by the responses of complex cells with various preferred directions. Simulation results demonstrate that the spiking neuron-based network effectively replicates the directional selectivity operation of the visual cortex when presented with a sequence of time-varying images. We evaluate the proposed model against state-of-the-art spiking neuron-based motion detection models using publicly available datasets. The results highlight the model\'s capability to extract motion energy from diverse video sequences, akin to human visual motion perception models. Additionally, we showcase the application of the proposed model in motion segmentation tasks and compare its performance with state-of-the-art motion-based segmentation models using challenging video segmentation benchmarks. The results indicate competitive performance. The motion maps generated by the proposed model can be utilized for action recognition in input videos.

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.

The collective behavior of animal groups emerges from the interactions among individuals. These social interactions produce the coordinated movements of bird flocks and fish schools, but little is known about their developmental emergence and neurobiological foundations. By characterizing the visually based schooling behavior of the micro glassfish Danionella cerebrum, we found that social development progresses sequentially, with animals first acquiring the ability to aggregate, followed by postural alignment with social partners. This social maturation was accompanied by the development of neural populations in the midbrain that were preferentially driven by visual stimuli that resemble the shape and movements of schooling fish. Furthermore, social isolation over the course of development impaired both schooling behavior and the neural encoding of social motion in adults. This work demonstrates that neural populations selective for the form and motion of conspecifics emerge with the experience-dependent development of collective movement.

The informal heuristic practices of the fine arts have much to offer to our understanding of the appearance of phenomenological reality. One interesting example is the use of exaggeration to enhance the illusion of liveliness in both living and nonliving subjects. This further eases the uncomfortable sense that the motion is somehow uncanny - especially with inanimate objects. We performed a series of experiments to test the effects of exaggeration on the phenomenological perception of simple animated objects - bouncing balls. A physically plausible model of a bouncing ball was augmented with a frequently used form of exaggeration known as squash and stretch. Observers were shown a series of animated balls, depicted using systematic parameterizations of the exaggeration model, and asked to rate their plausibility. A range of rendering styles provided varying levels of information as to the type of ball. In all cases, balls with small amounts of exaggeration were seen as plausible as those without any exaggeration (e.g., with veridical motion). Furthermore, when the type of ball was not specified, observers tolerated a large amount of exaggeration before judging them as implausible. When the type of ball was indicated, observers narrowed the range of acceptable exaggeration somewhat but still tolerated exaggeration well beyond that which would be physically possible. We contend that, in this case, exaggeration acts to bridge the so-called uncanny valley for artificial depictions of physical reality.

Moving frames produce large displacements in the perceived location of flashed and continuously moving probes. In a series of experiments, we test the contributions of the probe\'s displacement and the frame\'s displacement on the strength of the frame\'s effect. In the first experiment, we find a dramatic position shift of flashed probes whereas the effect on a continuously moving probe is only one-third as strong. In Experiment 2, we show that the absence of an effect for the static probe is a consequence of its perceptual grouping with the static background. As long as the continuously present probe has some motion, it appears to group to some extent with the frame and show an illusory shift of intermediate magnitude. Finally, we informally explored the illusory shifts seen for a continuously moving probe when the frame itself has a more complex path. In this case, the probe appears to group more strongly with the frame. Overall, the effects of the frame on the probe demonstrate the outcome of a competition between the frame and the static background in determining the frame of reference for the probe\'s perceived position.

BACKGROUND: Research has shown that visual perceptual learning (VPL) is related to modifying neural activity in higher level decision-making regions. However, the causal roles of the prefrontal and visual cortexes in VPL are still unclear. Here, we investigated how anodal transcranial direct current stimulation (tDCS) of the prefrontal and visual cortices modulates VPL in the early and later phases and the role of multiple brain regions.
METHODS: Perceptual learning on the coherent motion direction identification task included early and later stages. After early training, participants needed to continuously train to reach a plateau; once the plateau was reached, participants entered a later stage. Sixty participants were randomly divided into five groups. Regardless of the training at the early and later stages, four groups received multitarget tDCS over the right dorsolateral prefrontal cortex (rDLPFC) and right middle temporal area (rMT), single-target tDCS over the rDLPFC, and single-target tDCS over the rMT or sham stimulation, and one group was stimulated at the ipsilateral brain region (i.e., left MT).
RESULTS: Compared with sham stimulation, multitarget and two single-target tDCS over the rDLPFC or rMT improved posttest performance and accelerated learning during the early period. However, multitarget tDCS and two single-target tDCS led to equivalent benefits for VPL. Additionally, these beneficial effects were absent when anodal tDCS was applied to the ipsilateral brain region. For the later period, the above facilitating effects on VPL induced by multitarget or single-target tDCS disappeared.
CONCLUSIONS: This study suggested the causal role of the prefrontal and visual cortices in visual motion perceptual learning by anodal tDCS but failed to find greater beneficial effects by simultaneously stimulating the prefrontal and visual cortices. Future research should investigate the functional associations between multiple brain regions to further promote VPL.

Massive studies have explored biological motion (BM) crowds processing for their remarkable social significance, primarily focused on uniformly distributed ones. However, real-world BM crowds often exhibit hierarchical structures rather than uniform arrangements. How such structured BM crowds are processed remains a subject of inquiry. This study investigates the representation of structured BM crowds in working memory (WM), recognizing the pivotal role WM plays in our social interactions involving BM. We propose the group-based ensemble hypothesis and test it through a member identification task. Participants were required to discern whether a presented BM belonged to a prior memory display of eight BM, each with distinct walking directions. Drawing on prominent Gestalt principles as organizational cues, we constructed structured groups within BM crowds by applying proximity and similarity cues in Experiments 1 and 2, respectively. In Experiment 3, we deliberately weakened the visibility of stimuli structures by increasing the similarity between subsets, probing the robustness of results. Consistently, our findings indicate that BM aligned with the mean direction of the subsets was more likely to be recognized as part of the memory stimuli. This suggests that WM inherently organizes structured BM crowds into separate ensembles based on organizational cues. In essence, our results illuminate the simultaneous operation of grouping and ensemble encoding mechanisms for BM crowds within WM.

When people indicate the vanishing location of a moving target that suddenly disappears, systematic errors forward (in the direction of motion) and downward (in the direction of gravity) emerge. These spatial displacements were coined, respectively, Representational Momentum and Representational Gravity, and are believed to reflect internalized ecologically relevant physical invariants useful for the anticipation of future states of an event. Previous research has shown that sports athletes exhibit increased Representational Momentum, indicating enhanced motion extrapolation and anticipation, albeit it is still not clear up to what degree this effect is specific for the expertise context or if it generalizes to other dynamic events. Furthermore, the influence of expertise on Representational Gravity, particularly in contexts where anticipation of vertically moving objects is crucial, remains understudied. This study aimed to address these gaps by focusing on Volleyball as a context of expertise due to the prevalence of fast vertically moving balls. Volleyball athletes and non-athletes indicated the perceived offset location of a smoothly moving target, which moved at a constant speed or was subjected to acceleration/deceleration, embedded either in a Volleyball or neutral context. Outcomes revealed that for the Volleyball context, athletes, but not non-athletes, revealed a significant trend to misperceive targets moving along the left diagonal to be further displaced forward beyond what would be expected due to Representational Momentum alone. This finding is discussed in relation to the natural statistics of Volleyball games, where crossed ball trajectories, particularly by the outside hitter, are more prevalent, fast, and offensive, requiring better anticipation to be efficiently dealt with.

The ability to make accurate and timely decisions, such as judging when it is safe to cross the road, is the foundation of adaptive behavior. While the computational and neural processes supporting simple decisions on isolated stimuli have been well characterized, decision-making in the real world often requires integration of discrete sensory events over time and space. Most previous experimental work on perceptual decision-making has focused on tasks that involve only a single, task-relevant source of sensory input. It remains unclear, therefore, how such integrative decisions are regulated computationally. Here we used psychophysics, electroencephalography, and computational modeling to understand how the human brain combines visual motion signals across space in the service of a single, integrated decision. To that purpose, we presented two random-dot kinematograms in the left and the right visual hemifields. Coherent motion signals were shown briefly and concurrently in each location, and healthy adult human participants of both sexes reported the average of the two motion signals. We directly tested competing predictions arising from influential serial and parallel accounts of visual processing. Using a biologically plausible model of motion filtering, we found evidence in favor of parallel integration as the fundamental computational mechanism regulating integrated perceptual decisions.