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Objective: Previous studies have found that patients with Major Depressive Disorder (MDD) exhibit impaired visual motion perception capabilities, and multi-level abnormalities in the human middle temporal complex (MT+), a key brain area for processing visual motion information. However, the brain activity pattern of MDD patients during the perception of visual motion information is currently unclear. In order to study the effect of depression on the activity and functional connectivity (FC) of MT+ during the perception of visual motion information, we conducted a study combining task-state fMRI and psychophysical paradigm to compare MDD patients and healthy control (HC). Methods: Duration threshold was examined through a visual motion perception psychophysical experiment. In addition, a classic block-design grating motion task was utilized for fMRI scanning of 24 MDD patients and 25 HC. The grating moved randomly in one of eight directions. We examined the neural activation under visual stimulation conditions compared to the baseline and FC. Results: Compared to HC group, MDD patients exhibited increased duration threshold. During the task, MDD patients showed decreased beta value and percent signal change in left and right MT+. In the sample comprising MDD and HC, there was a significant negative correlation between beta value in right MT+ and duration threshold. And in MDD group, activation in MT+ were significantly correlated with retardation score. Notably, no such differences in activation were observed in primary visual cortex (V1). Furthermore, when left MT+ served as the seed region, compared to the HC, MDD group showed increased FC with right calcarine fissure and surrounding cortex and decreased FC with left precuneus. Conclusion: Overall, the findings of this study highlight that the visual motion perception function impairment in MDD patients relates to abnormal activation patterns in MT+, and task-related activity are significantly connected to the retardation symptoms of the disease. This not only provides insights into the potential neurobiological mechanisms behind visual motion perception disorder in MDD patients from the aspect of task-related brain activity, but also supports the importance of MT+ as a candidate biomarker region for MDD. [ABSTRACT FROM AUTHOR]

Human vision is remarkably good at recovering the latent hierarchical structure of dynamic scenes. Here, we explore how visual attention operates with this hierarchical motion representation. The way in which attention responds to surface physical features has been extensively explored. However, we know little about how the distribution of attention can be distorted by the latent hierarchical structure. To explore this topic, we conducted two experiments to investigate the relationship between minimal graph distance (MGD), one key factor in hierarchical representation, and attentional distribution. In Experiment 1, we constructed three hierarchical structures consisting of two moving objects with different MGDs. In Experiment 2, we generated three moving objects from one hierarchy to eliminate the influence of different structures. Attention was probed by the classic congruent–incongruent cueing paradigm. Our results show that the cueing effect is significantly smaller when the MGD between two objects is shorter, which suggests that attention is not evenly distributed across multiple moving objects but distorted by their latent hierarchical structure. As neither the latent structure nor the graph distance was part of the explicit task, our results also imply that both the construction of hierarchical representation and the attention to that representation are spontaneous and automatic. [ABSTRACT FROM AUTHOR]

The purpose of the current study was to clarify the effect of eccentricity on visual motion prediction using a time‐to‐contact (TTC) task. TTC indicates the predictive ability to accurately estimate the time‐to‐contact of a moving object based on visual motion perception. We also measured motion reaction time (motion RT) as an indicator of the speed of visual motion perception. The TTC task was to press a button when the moving target would arrive at the stationary goal. In the occluded condition, the target dot was occluded 500 ms before the time to contact. The motion RT task was to press a button as soon as the target moved. The visual targets were randomly presented at five different eccentricities (4°, 6°, 8°, 10°, 12°) and moved on a circular trajectory at a constant tangent velocity (8°/s) to keep the eccentricity constant. Our results showed that TTC in the occluded condition showed an earlier response as the eccentricity increased. Furthermore, the motion RT became longer as the eccentricity increased. Therefore, it is most likely that a slower speed perception in peripheral vision delays the perceived speed of motion onset and leads to an earlier response in the TTC task. [ABSTRACT FROM AUTHOR]

During natural viewing, we often recognize multiple objects, detect their motion, and select one object as the target to track. It remains to be determined how such behavior is guided by the integration of visual form and motion perception. To address this, we studied how monkeys made a choice to track moving targets with different forms by smooth pursuit eye movements in a two-target task. We found that pursuit responses were biased toward the motion direction of a target with a hole. By computing the relative weighting, we found that the target with a hole exhibited a larger weight for vector computation. The global hole feature dominated other form properties. This dominance failed to account for changes in pursuit responses to a target with different forms moving singly. These findings suggest that the integration of visual form and motion perception can reshape the competition in sensorimotor networks to guide behavioral selection. [ABSTRACT FROM AUTHOR]

Following a unilateral post-chiasmal lesion of the geniculo-striate pathway, patients develop homonymous visual field defects. Using classical perimetry, patients with 'complete' homonymous hemianopia are unaware of stimuli in the affected hemifield. However, some show preserved vision in the affected hemifield in which the conscious perception of moving stimuli is preserved (Riddoch phenomenon). Prior evidence suggests that preservation of a direct pathway from the lateral geniculate nucleus to visual area 5 (bypassing the primary visual cortex) may be the basis of this type of residual vision. The aim of the present study was to investigate the possibility of a correlation between preserved motion perception in hemianopia and the fibre connectivity density of the underlying pathways. This research was a case-control study carried out in a tertiary care centre between 2019 and 2021. Participants ( n = 48) were divided into two groups: patients with homonymous visual field defects ( n = 20) and normal controls ( n = 28). All participants underwent Humphrey field analysis (outcome = visual field index); kinetic perimetry (outcome = %correct); brain MRI; and diffusion tensor imaging probabilistic tractography (outcome = fibre connectivity density). The difference between %correct in kinetic perimetry and visual field index in Humphrey field analysis provided an indication of the level of preserved motion perception. A significant positive correlation was found between the fibre connectivity density of contralateral lateral geniculate nucleus-contralateral visual area 5 and the preserved motion perception (rho = 0.5965, P < 0.0012) and between the fibre connectivity density of contralateral visual area 5-contralateral lateral geniculate nucleus and the preserved motion perception (rho = 0.5635, P < 0.0012) after adjusting with the Bonferroni method. The area under the curve was 0.7947 for the preserved motion perception in reflecting the fibre connectivity density of contralateral lateral geniculate nucleus-contralateral visual area 5, and 0.7660 for the preserved motion perception in reflecting the fibre connectivity density of contralateral visual area 5-contralateral lateral geniculate nucleus. We have demonstrated an extensive network of pathways connecting visual areas in the two hemispheres via the splenium of the corpus callosum. To our knowledge, this is the first report of a correlation between the preserved motion perception and the fibre connectivity density of the pathways underlying the Riddoch Phenomenon (specifically bilateral lateral geniculate nuclei to visual area 5 contralateral to the lesion). The difference between %correct in kinetic perimetry and visual field index measures the preserved motion perception and is related to the underlying neural damage. The methodology has the potential to evaluate and monitor patients with hemianopia., Competing Interests: The authors report no competing interests., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Objective To investigate the effect of short-term badminton training on global motion perception (GMP) in adults. Methods 21 participants in the training group were all members of the badminton training class, and 20 participants in the control group were ordinary undergraduates. The training group received 10 weeks of badminton training, and the control group did not carry out any regular physical training. Both groups completed the landing point perception task of a flying shuttle and the GMP task. Results The training group showed a significantly higher accuracy in the landing point judgement task and a lower threshold value in the GMP task than those before the training; while the control group did not exhibit similar changes. Conclusion The short-term badminton training may improve not only adults' performance in training-related visual motion perception tasks, but their performance in more general and training-independent tasks (e.g., GMP task). The visual motion perception experience accumulated by badminton training may be better in terms of transferability. [ABSTRACT FROM AUTHOR]

Similar to most visual animals, the crab Neohelice granulata relies predominantly on visual information to escape from predators, to track prey and for selecting mates. It, therefore, needs specialized neurons to process visual information and determine the spatial location of looming objects. In the crab Neohelice granulata, the Monostratified Lobula Giant type1 (MLG1) neurons have been found to manifest looming sensitivity with finely tuned capabilities of encoding spatial location information. MLG1s neuronal ensemble can not only perceive the location of a looming stimulus, but are also thought to be able to influence the direction of movement continuously, for example, escaping from a threatening, looming target in relation to its position. Such specific characteristics make the MLG1s unique compared to normal looming detection neurons in invertebrates which can not localize spatial looming. Modeling the MLG1s ensemble is not only critical for elucidating the mechanisms underlying the functionality of such neural circuits, but also important for developing new autonomous, efficient, directionally reactive collision avoidance systems for robots and vehicles. However, little computational modeling has been done for implementing looming spatial localization analogous to the specific functionality of MLG1s ensemble. To bridge this gap, we propose a model of MLG1s and their pre-synaptic visual neural network to detect the spatial location of looming objects. The model consists of 16 homogeneous sectors arranged in a circular field inspired by the natural arrangement of 16 MLG1s' receptive fields to encode and convey spatial information concerning looming objects with dynamic expanding edges in different locations of the visual field. Responses of the proposed model to systematic real-world visual stimuli match many of the biological characteristics of MLG1 neurons. The systematic experiments demonstrate that our proposed MLG1s model works effectively and robustly to perceive and localize looming information, which could be a promising candidate for intelligent machines interacting within dynamic environments free of collision. This study also sheds light upon a new type of neuromorphic visual sensor strategy that can extract looming objects with locational information in a quick and reliable manner.

Similar to most visual animals, the crab Neohelice granulata relies predominantly on visual information to escape from predators, to track prey and for selecting mates. It, therefore, needs specialized neurons to process visual information and determine the spatial location of looming objects. In the crab Neohelice granulata , the Monostratified Lobula Giant type1 (MLG1) neurons have been found to manifest looming sensitivity with finely tuned capabilities of encoding spatial location information. MLG1s neuronal ensemble can not only perceive the location of a looming stimulus, but are also thought to be able to influence the direction of movement continuously, for example, escaping from a threatening, looming target in relation to its position. Such specific characteristics make the MLG1s unique compared to normal looming detection neurons in invertebrates which can not localize spatial looming. Modeling the MLG1s ensemble is not only critical for elucidating the mechanisms underlying the functionality of such neural circuits, but also important for developing new autonomous, efficient, directionally reactive collision avoidance systems for robots and vehicles. However, little computational modeling has been done for implementing looming spatial localization analogous to the specific functionality of MLG1s ensemble. To bridge this gap, we propose a model of MLG1s and their pre-synaptic visual neural network to detect the spatial location of looming objects. The model consists of 16 homogeneous sectors arranged in a circular field inspired by the natural arrangement of 16 MLG1s' receptive fields to encode and convey spatial information concerning looming objects with dynamic expanding edges in different locations of the visual field. Responses of the proposed model to systematic real-world visual stimuli match many of the biological characteristics of MLG1 neurons. The systematic experiments demonstrate that our proposed MLG1s model works effectively and robustly to perceive and localize looming information, which could be a promising candidate for intelligent machines interacting within dynamic environments free of collision. This study also sheds light upon a new type of neuromorphic visual sensor strategy that can extract looming objects with locational information in a quick and reliable manner. [ABSTRACT FROM AUTHOR]

Although numerous models describe the individual neural mechanisms that may be involved in the perception of visual motion, few of them have been constructed to take arbitrary stimuli and map them to a motion percept. Here, we propose an integrated dynamical motion model (IDM), which is sufficiently general to handle diverse moving stimuli, yet sufficiently precise to account for a wide-ranging set of empirical observations made on a family of random dot kinematograms. In particular, we constructed models of the cortical areas involved in motion detection, motion integration and perceptual decision. We analyzed their parameters through dynamical simulations and numerical continuation to constrain their proper ranges. Then, empirical data from a family of random dot kinematograms experiments with systematically varying direction distribution, presentation duration and stimulus size, were used to evaluate our model and estimate corresponding model parameters. The resulting model provides an excellent account of a demanding set of parametrically varied behavioral effects on motion perception, providing both quantitative and qualitative elements of evaluation.

The perception of different visual motion cues is crucial for autonomous mobile robots to react to or interact with the dynamic visual world. It is still a great challenge for a micro mobile robot to cope with dynamic environments due to the restricted computational resources and the limited functionalities of its visual systems. In this study, we propose a compound visual neural system to automatically extract and fuse different visual motion cues in real-time using the extremely constrained computation power of micro mobile robots. The proposed visual system contains multiple bio-inspired visual motion perceptive neurons each with a unique role, for example to extract collision visual cues, darker collision cue and directional motion cues. In the embedded system, these multiple visual neurons share a similar presynaptic network to minimise the consumption of computation resources. In the postsynaptic part of the system, visual cues pass results to corresponding action neurons using lateral inhibition mechanism. The translational motion cues, which are identified by comparing pairs of directional cues, are given the highest priority, followed by the darker colliding cues and approaching cues. Systematic experiments with both virtual visual stimuli and real-world scenarios have been carried out to validate the system's functionality and reliability. The proposed methods have demonstrated that (1) with extremely limited computation power, it is still possible for a micro mobile robot to extract multiple visual motion cues robustly in a complex dynamic environment; (2) the cues extracted can be fused with a lateral inhibited postsynaptic network, thus enabling the micro robots to respond effectively with different actions, accordingly to different states, in real-time. The proposed embedded visual system has been modularised and can be easily implemented in other autonomous mobile platforms for real-time applications. The system could also be used by neurophysiologists to test new hypotheses pertaining to biological visual neural systems.

In primates' cerebral cortex, depth rotation sensitive (DRS) neurons have the property of preferential selectivity for depth rotation motion, whereas such a property is rarely adopted to create computational models for depth rotation motion detection. To fill this gap, a novel feedforward visual neural network is developed to execute depth rotation object detection, based on the recent neurophysiologic achievements on the mammalian vision system. The proposed neural network consists of two parts, i.e., presynaptic and postsynaptic neural networks. The former comprises multiple lateral inhibition neural sub-networks for the capture of visual motion information, and the latter extracts the cues of translational and depth motion and later, synthesizes such clues to perceive the process of depth rotation of an object. Experimentally, the neural network is sufficiently examined by different types of depth rotation under multiple conditions and settings. Numerical experiments show that not only it can effectively detect the spatio-temporal energy change of depth rotation of a moving object, but also its output excitation curve is a quasi-sinusoidal one, which is compatible with the hypothesis suggested by Johansson and Jansson in projective geometry. This research is a critical step toward the construction of artificial vision system for depth rotation object recognition. [ABSTRACT FROM AUTHOR]

Traditionally, the visual motion area (MT) is considered as a brain region specialized for visual motion perception. However, accumulating evidence showed that MT is also related to various functions, suggesting that it is a complex functional area and different functional subregions might exist in this area. To delineate functional subregions of this area, left and right masks of MT were defined using meta-analysis in the BrainMap database, and coactivation-based parcellation was then performed on these two masks. Two dorsal subregions (Cl1 and Cl2) and one ventral subregion (Cl3) of left MT, as well as two dorsal-anterior subregions (Cl1 and Cl2), one ventral-anterior subregion (Cl3), and an additional posterior subregion (Cl4) of right MT were identified. In addition to vision motion, distinct and specific functions were identified in different subregions characterized by task-dependent functional connectivity mapping and forward/reverse inference on associated functions. These results not only were in accordance with the previous findings of a hemispheric asymmetry of MT, but also strongly confirmed the existence of subregions in this region with distinct and specific functions. Furthermore, our results extend the special role of visual motion perception on this area and might facilitate future cognitive study.

Abstract Background Falls are the leading cause of accidental injury and death among older adults. One of three adults over the age of 65 years falls annually. As the size of elderly population increases, falls become a major concern for public health and there is a pressing need to understand the causes of falls thoroughly. Main body of the abstract While it is well documented that visual functions such as visual acuity, contrast sensitivity, and stereo acuity are correlated with fall risks, little attention has been paid to the relationship between falls and the ability of the visual system to perceive motion in the environment. The omission of visual motion perception in the literature is a critical gap because it is an essential function in maintaining balance. In the present article, we first review existing studies regarding visual risk factors for falls and the effect of ageing vision on falls. We then present a group of phenomena such as vection and sensory reweighting that provide information on how visual motion signals are used to maintain balance. Conclusion We suggest that the current list of visual risk factors for falls should be elaborated by taking into account the relationship between visual motion perception and balance control.

Visually induced self-motion perception (vection) relies on visual–vestibular interaction. Imaging studies using vestibular stimulation have revealed a vestibular thalamo-cortical dominance in the right hemisphere in right handers and the left hemisphere in left handers. We investigated if the behavioural characteristics and neural correlates of vection differ between healthy left and right-handed individuals. 64-channel EEG was recorded while 25 right handers and 25 left handers were exposed to vection-compatible roll motion (coherent motion) and a matched, control condition (incoherent motion). Behavioural characteristics, i.e. vection presence, onset latency, duration and subjective strength, were also recorded. The behavioural characteristics of vection did not differ between left and right handers (all p > 0.05). Fast Fourier Transform (FFT) analysis revealed significant decreases in alpha power during vection–compatible roll motion (p < 0.05). The topography of this decrease was handedness-dependent, with left handers showing a left lateralized centro-parietal decrease and right handers showing a bilateral midline centro-parietal decrease. Further time–frequency analysis, time locked to vection onset, revealed a comparable decrease in alpha power around vection onset and a relative increase in alpha power during ongoing vection, for left and right handers. No effects were observed in theta and beta bands. Left and right-handed individuals show vection-related alpha power decreases at different topographical regions, possibly related to the influence of handedness-dependent vestibular dominance in the visual–vestibular interaction that facilitates visual self-motion perception. Despite this difference in where vection-related activity is observed, left and right handers demonstrate comparable perception and underlying alpha band changes during vection. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to use deep neural networks to decode the electroencephalography (EEG) signals evoked when individuals perceive four types of motion stimuli (contraction, expansion, rotation, and translation). Methods for single-trial and multi-trial EEG classification are both investigated in this study. Attention mechanisms and a variant of recurrent neural networks (RNNs) are incorporated as the decoding model. Attention mechanisms emphasize task-related responses and reduce redundant information of EEG, whereas RNN learns feature representations for classification from the processed EEG data. To promote generalization of the decoding model, a novel online data augmentation method that randomly averages EEG sequences to generate artificial signals is proposed for single-trial EEG. For our dataset, the data augmentation method improves the accuracy of our model (based on RNN) and two benchmark models (based on convolutional neural networks) by 5.60%, 3.92%, and 3.02%, respectively. The attention-based RNN reaches mean accuracies of 67.18% for single-trial EEG decoding with data augmentation. When performing multi-trial EEG classification, the amount of training data decreases linearly after averaging, which may result in poor generalization. To address this deficiency, we devised three schemes to randomly combine data for network training. Accordingly, the results indicate that the proposed strategies effectively prevent overfitting and improve the correct classification rate compared with averaging EEG fixedly (by up to 19.20%). The highest accuracy of the three strategies for multi-trial EEG classification achieves 82.92%. The decoding performance for the methods proposed in this work indicates they have application potential in the brain–computer interface (BCI) system based on visual motion perception. [ABSTRACT FROM AUTHOR]

Traditionally, the visual motion area (MT) is considered as a brain region specialized for visual motion perception. However, accumulating evidence showed that MT is also related to various functions, suggesting that it is a complex functional area and different functional subregions might exist in this area. To delineate functional subregions of this area, left and right masks of MT were defined using meta-analysis in the BrainMap database, and coactivation-based parcellation was then performed on these two masks. Two dorsal subregions (Cl1 and Cl2) and one ventral subregion (Cl3) of left MT, as well as two dorsal-anterior subregions (Cl1 and Cl2), one ventral-anterior subregion (Cl3), and an additional posterior subregion (Cl4) of right MT were identified. In addition to vision motion, distinct and specific functions were identified in different subregions characterized by task-dependent functional connectivity mapping and forward/reverse inference on associated functions. These results not only were in accordance with the previous findings of a hemispheric asymmetry of MT, but also strongly confirmed the existence of subregions in this region with distinct and specific functions. Furthermore, our results extend the special role of visual motion perception on this area and might facilitate future cognitive study. [ABSTRACT FROM AUTHOR]

Following moving visual stimuli (conditioning stimuli, CS), many organisms perceive, in the absence of physical stimuli, illusory motion in the opposite direction. This phenomenon is known as the motion aftereffect (MAE). Here, we use MAE as a tool to study the neuronal basis of visual motion perception in zebrafish larvae. Using zebrafish eye movements as an indicator of visual motion perception, we find that larvae perceive MAE. Blocking eye movements using optogenetics during CS presentation did not affect MAE, but tectal ablation significantly weakened it. Using two-photon calcium imaging of behaving GCaMP3 larvae, we find post-stimulation sustained rhythmic activity among direction-selective tectal neurons associated with the perception of MAE. In addition, tectal neurons tuned to the CS direction habituated, but neurons in the retina did not. Finally, a model based on competition between direction-selective neurons reproduced MAE, suggesting a neuronal circuit capable of generating perception of visual motion.

The main objective of this paper is to use deep neural networks to decode the electroencephalography (EEG) signals evoked when individuals perceive four types of motion stimuli (contraction, expansion, rotation, and translation). Methods for single-trial and multi-trial EEG classification are both investigated in this study. Attention mechanisms and a variant of recurrent neural networks (RNNs) are incorporated as the decoding model. Attention mechanisms emphasize task-related responses and reduce redundant information of EEG, whereas RNN learns feature representations for classification from the processed EEG data. To promote generalization of the decoding model, a novel online data augmentation method that randomly averages EEG sequences to generate artificial signals is proposed for single-trial EEG. For our dataset, the data augmentation method improves the accuracy of our model (based on RNN) and two benchmark models (based on convolutional neural networks) by 5.60%, 3.92%, and 3.02%, respectively. The attention-based RNN reaches mean accuracies of 67.18% for single-trial EEG decoding with data augmentation. When performing multi-trial EEG classification, the amount of training data decreases linearly after averaging, which may result in poor generalization. To address this deficiency, we devised three schemes to randomly combine data for network training. Accordingly, the results indicate that the proposed strategies effectively prevent overfitting and improve the correct classification rate compared with averaging EEG fixedly (by up to 19.20%). The highest accuracy of the three strategies for multi-trial EEG classification achieves 82.92%. The decoding performance for the methods proposed in this work indicates they have application potential in the brain–computer interface (BCI) system based on visual motion perception.

Extracting common patterns of neural circuit computations in the autism spectrum and confirming them as a cause of specific core traits of autism is the first step toward identifying cell-level and circuit-level targets for effective clinical intervention. Studies in humans with autism have identified functional links and common anatomic substrates between core restricted behavioral repertoire, cognitive rigidity, and overstability of visual percepts during visual rivalry. To study these processes with single-cell precision and comprehensive neuronal population coverage, we developed the visual bistable perception paradigm for mice based on ambiguous moving plaid patterns consisting of two transparent gratings drifting at an angle of 120°. This results in spontaneous reversals of the perception between local component motion (plaid perceived as two separate moving grating components) and integrated global pattern motion (plaid perceived as a fused moving texture). This robust paradigm does not depend on the explicit report of the mouse, since the direction of the optokinetic nystagmus (OKN) is used to infer the dominant percept. Using this paradigm, we found that the rate of perceptual reversals between global and local motion interpretations is reduced in the methyl-CpG-binding protein 2 duplication syndrome (MECP2-ds) mouse model of autism. Moreover, the stability of local motion percepts is greatly increased in MECP2-ds mice at the expense of global motion percepts. Thus, our model reproduces a subclass of the core features in human autism (reduced rate of visual rivalry and atypical perception of visual motion). This further offers a well-controlled approach for dissecting neuronal circuits underlying these core features., Competing Interests: The authors declare no competing financial interests., (Copyright © 2024 Bogatova et al.)

Neurophysiological studies validate that the primate cerebral cortex includes spiral neurons whose visual properties respond preferentially to spiral motion patterns. However, the biological mechanism of which a vision system perceives spiral motion is unclear, while few computational models are reported to discuss the problem of spiral motion perception. In order to fill this gap, this work develops a spiral motion perception neural network in terms of the recent achievements in neurophysiology and simulates the visual response characteristics of spiral neurons. One such network, inspired by two stages of biological visual information processing includes two subnetworks- presynaptic and postsynaptic neural networks. The former comprises multiple lateral inhibition neural sub-networks for the capture of visual motion information, whereas the latter extracts different rotational and radial motion cues and synthesizes them to detect the process of the spiral motion of an object. Experimentally, the proposed neural network is sufficiently examined by different types of spiral motion patterns in non-interference or interference environments. Numerically comparative experiments show that it can effectively detect spiral motion patterns of the object and also does not respond to any non-spiral motion, which is consistent with the metaphor of spiral neurons’ performance perception. [ABSTRACT FROM AUTHOR]

Transcranial direct current stimulation (tDCS) has the potential to benefit visual perceptual learning (VPL). However, previous studies investigated the effect of tDCS on VPL within early sessions, and the influence of tDCS on learning effects at later stages (plateau level) is unclear. Here, participants completed 9 days of training on coherent motion direction identification to reach a plateau (stage 1) and then continued training for 3 days (stage 2). The coherent thresholds were measured before training, after stage 1 and after stage 2. In the first group, anodal tDCS was applied when participants trained over a period of 12 days (stage 1 + stage 2). In the second group, participants completed a 9-day training period without any stimulation to reach a plateau (stage 1); after that, participants completed a 3-day training period while anodal tDCS was administered (stage 2). The third group was treated the same as the second group except that anodal tDCS was replaced by sham tDCS. The results showed that anodal tDCS did not improve posttest performance after the plateau was reached. The comparison of learning curves between the first and third groups showed that anodal tDCS decreased the threshold at the early stage, but it did not improve the plateau level. For the second and third groups, anodal tDCS did not further enhance the plateau level after a continued 3-day training period. These results suggest that anodal tDCS boosts VLP during the early period of training sessions, but it fails to facilitate later learning effects. This study contributed to a deep understanding of the dissociable tDCS effects at distinct temporal stages, which may be due to the dynamic change in brain regions during the time course of VPL. • Anodal tDCS facilitated multisession visual motion learning at the early stage. • Anodal tDCS did not improve the later learning effects. • The dissociable tDCS effects may be due to the dynamic change in brain regions. [ABSTRACT FROM AUTHOR]

The visual motion aftereffect is a visual illusion in which exposure to continuous motion in one direction leads to a subsequent illusion of visual motion in the opposite direction. Previous findings have been mixed with regard to whether this visual illusion can be induced cross-modally by auditory stimuli. Based on research on multisensory perception demonstrating the profound influence auditory perception can have on the interpretation and perceived motion of visual stimuli, we hypothesized that exposure to auditory stimuli with strong directional motion cues should induce a visual motion aftereffect. Here, we demonstrate that horizontally moving auditory stimuli induced a significant visual motion aftereffect—an effect that was driven primarily by a change in visual motion perception following exposure to leftward moving auditory stimuli. This finding is consistent with the notion that visual and auditory motion perception rely on at least partially overlapping neural substrates.

During infancy, smart perceptual mechanisms develop allowing infants to judge time-space motion dynamics more efficiently with age and locomotor experience. This emerging capacity may be vital to enable preparedness for upcoming events and to be able to navigate in a changing environment. Little is known about brain changes that support the development of prospective control and about processes, such as preterm birth, that may compromise it. As a function of perception of visual motion, this paper will describe behavioural and brain studies with young infants investigating the development of visual perception for prospective control. By means of the three visual motion paradigms of occlusion, looming, and optic flow, our research shows the importance of including behavioural data when studying the neural correlates of prospective control.

Recent studies have shown that interindividual variability can be a rich source of information regarding the mechanism of human visual perception. In this study, we examined the mechanisms underlying interindividual variability in the perception of visual motion, one of the fundamental components of visual scene analysis, by measuring neurotransmitter concentrations using magnetic resonance spectroscopy. First, by psychophysically examining two types of motion phenomena--motion assimilation and contrast--we found that, following the presentation of the same stimulus, some participants perceived motion assimilation,while others perceivedmotion contrast. Furthermore, we found that the concentration of the excitatory neurotransmitter glutamate--glutamine (Glx) in the dorsolateral prefrontal cortex (Brodmann area 46) was positively correlated with the participant's tendency to motion assimilation over motion contrast; however, this effect was not observed in the visual areas. The concentration of the inhibitory neurotransmitter ♈-aminobutyric acid had only a weak effect compared with that of Glx.We conclude that excitatory process in the suprasensory area is important for an individual's tendency to determine antagonistically perceived visual motion phenomena. [ABSTRACT FROM AUTHOR]

The visual motion aftereffect is a visual illusion in which exposure to continuous motion in one direction leads to a subsequent illusion of visual motion in the opposite direction. Previous findings have been mixed with regard to whether this visual illusion can be induced cross-modally by auditory stimuli. Based on research on multisensory perception demonstrating the profound influence auditory perception can have on the interpretation and perceived motion of visual stimuli, we hypothesized that exposure to auditory stimuli with strong directional motion cues should induce a visual motion aftereffect. Here, we demonstrate that horizontally moving auditory stimuli induced a significant visual motion aftereffect--an effect that was driven primarily by a change in visual motion perception following exposure to leftward moving auditory stimuli. This finding is consistent with the notion that visual and auditory motion perception rely on at least partially overlapping neural substrates. [ABSTRACT FROM AUTHOR]

Summary Following moving visual stimuli (conditioning stimuli, CS), many organisms perceive, in the absence of physical stimuli, illusory motion in the opposite direction. This phenomenon is known as the motion aftereffect (MAE). Here, we use MAE as a tool to study the neuronal basis of visual motion perception in zebrafish larvae. Using zebrafish eye movements as an indicator of visual motion perception, we find that larvae perceive MAE. Blocking eye movements using optogenetics during CS presentation did not affect MAE, but tectal ablation significantly weakened it. Using two-photon calcium imaging of behaving GCaMP3 larvae, we find post-stimulation sustained rhythmic activity among direction-selective tectal neurons associated with the perception of MAE. In addition, tectal neurons tuned to the CS direction habituated, but neurons in the retina did not. Finally, a model based on competition between direction-selective neurons reproduced MAE, suggesting a neuronal circuit capable of generating perception of visual motion. [ABSTRACT FROM AUTHOR]

The diagnosis and treatment of the possible visual sequelae in those with traumatic brain injury (TBI) represents an important area of health care in this special population. One of their most prevalent yet elusive visual symptoms is visual motion sensitivity (VMS). In this review, we present the basic VMS phenomenon and its related symptoms, clinical studies in the area, clinical research investigations using the visual-evoked potential (VEP) as a cortical probe, and possible mechanisms and related neurophysiology that may underlie VMS. Lastly, therapeutic interventions are briefly described, as well as future directions for clinical research and patient care in those with VMS and TBI.

During infancy, smart perceptual mechanisms develop allowing infants to judge time- space motion dynamics more efficiently with age and locomotor experience. This emerging capacity may be vital to enable preparedness for upcoming events and to be able to navigate in a changing environment. Little is known about brain changes that support the development of prospective control and about processes, such as preterm birth, that may compromise it. As a function of perception of visual motion, this paper will describe behavioral and brain studies with young infants investigating the development of visual perception for prospective control. By means of the three visual motion paradigms of occlusion, looming, and optic flow, our research shows the importance of including behavioral data when studying the neural correlates of prospective control. [ABSTRACT FROM AUTHOR]

Background: Schizophrenia patients exhibit deficient processing of perceptual and cognitive information. However, it is not well understood how basic perceptual deficits contribute to higher level cognitive problems in this mental disorder. Perception of biological motion, a motion-based cognitive recognition task, relies on both basic visual motion processing and social cognitive processing, thus providing a useful paradigm to evaluate the potentially hierarchical relationship between these two levels of information processing. Methods: In this study, we designed a biological motion paradigm in which basic visual motion signals were manipulated systematically by incorporating different levels of motion noise. We measured the performances of schizophrenia patients (n=21) and healthy controls (n=22) in this biological motion perception task, as well as in coherent motion detection, theory of mind, and a widely used biological motion recognition task. Results: Schizophrenia patients performed the biological motion perception task with significantly lower accuracy than healthy controls when perceptual signals were moderately degraded by noise. A more substantial degradation of perceptual signals, through using additional noise, impaired biological motion perception in both groups. Performance levels on biological motion recognition, coherent motion detection and theory of mind tasks were also reduced in patients. Conclusion: The results from the motion-noise biological motion paradigm indicate that in the presence of visual motion noise, the processing of biological motion information in schizophrenia is deficient. Combined with the results of poor basic visual motion perception (coherent motion task) and biological motion recognition, the association between basic motion signals and biological motion perception suggests a need to incorporate the improvement of visual motion perception in social cognitive remediation.

Verb-related activity is consistently found in the left posterior lateral cortex (PLTC), encompassing also regions that respond to visual-motion perception. Besides motion, those regions appear sensitive to distinctions among the entities beyond motion, including that between first- vs . third-person (“third-person bias”). In two experiments, using functional magnetic resonance imaging (fMRI), we studied whether the implied subject (first/third-person) and/or the semantic content (motor/non-motor) of verbs modulate the neural activity in the left PLTC-regions responsive during basic- and biological-motion perception. In those sites, we found higher activity for verbs than for nouns. This activity was modulated by the person (but not the semantic content) of the verbs, with stronger response to third- than first-person verbs. The third-person bias elicited by verbs supports a role of motion-processing regions in encoding information about the entity beyond (and independently from) motion, and sets in a new light the role of these regions in verb processing. [ABSTRACT FROM AUTHOR]

At present there are serious grounds to believe that the motion aftereffect is characteristic of all sensory systems involved in spatial orientation, and that motion adaptation in one sensory system causes changes in the other one, and that such adjustment is of critical adaptive significance. In this part of the review we report briefly outlined developments and the current state of studies of this issue in visual modality. The visual motion aftereffect has been studied more comprehensively as compared with other modalities. The main concepts about the mechanisms of this phenomenon and application of motion adaptation to studies of visual motion analysis at its different levels are actively used in current scientific literature to understand the mechanisms of this phenomenon in other sensory systems. A leading role of vision in spatial orientation is manifested in the intersensory interaction where visual motion adaptation brings about significant changes in perception in other modalities. [ABSTRACT FROM AUTHOR]

Migraine ranks as the third most common disease in the world and has caused significant losses of daily life abilities. Previously, people gave more attention to the pain of migraines and usually ignored the impairments of cognitive function in migraineurs. In the present study, a duration discrimination paradigm was used to assess the global and local biological motion perception in migraineurs and healthy controls. In the experiment, biological motion sequences and inanimate motion sequences (the inverted biological motion sequences) were sequentially presented on a screen. Observers were instructed to make a two-alternative forced choice to accurately indicate which interval (the first or the second) appeared longer. The stimuli involved global biological motion sequences and local biological motion sequences. The statistical analyses were conducted on the points of subjective equality that were obtained by fitting a psychometric function to each individual observer’s data. In migraineurs, global biological motion signals lengthened the perceived temporal duration (as occurs in normal people), whereas local biological motion signals did not have this temporal dilation effect. The results indicated that patients with migraine showed a deficit in local biological motion perception, whereas their global biological motion perception was comparable to that of healthy subjects. [ABSTRACT FROM AUTHOR]

Visual perception can be changed by co-occurring input from other sensory modalities. Here, we explored how self-generated finger movements (left-right or up-down key presses) affect visual motion perception. In Experiment 1, motion perception of a blinking bar was shifted in the direction of co-occurring hand motor movements, indicative of motor-induced visual motion (MIVM). In Experiment 2, moving and static blinking bars were combined with either directional moving or stationary hand motor movements. Results showed that the directional component in the hand movement was crucial for MIVM as stationary motor movements even declined visual motion perception. In Experiment 3, the role of response bias was excluded in a two-alternative forced-choice task that ruled out the effect of response strategies. All three experiments demonstrated that alternating key presses (either horizontally or vertically aligned) induce illusory visual motion and that stationary motor movements (without a vertical or horizontal direction) induce the opposite effect, namely a decline in visual motion (more static) perception. [ABSTRACT FROM AUTHOR]

Our ability to perceive visual motion is critically dependent on the human motion complex (hMT+) in the dorsal visual stream. Extensive electrophysiological research in the monkey equivalent of this region has demonstrated how neuronal populations code for properties such as speed and direction, and that neurometric functions relate to psychometric functions within the individual monkey. In humans, the physiological correlates of inter-individual perceptual differences are still largely unknown. To address this question, we used functional magnetic resonance imaging (fMRI) while participants viewed translational motion in different directions, and we measured thresholds for direction discrimination of moving stimuli in a separate psychophysics experiment. After determining hMT+ in each participant with a functional localizer, we were able to decode the different directions of visual motion from it using pattern classification (PC). We also characterized the variability of fMRI signal in hMT+ during stimulus and rest periods with a generative model. Relating perceptual performance to physiology, individual direction discrimination thresholds were significantly correlated with the variability measure in hMT+, but not with PC accuracies. Individual differences in PC accuracy were driven by non-physiological noise like head-movement, which makes this method a poor tool to investigate inter-individual differences. In contrast, variability analysis of the fMRI signal was robust to non-physiological noise, and variability characteristics in hMT+ correlated with psychophysical thresholds in the individual participants. Higher levels of fMRI signal variability compared to rest correlated with lower discrimination thresholds. This result is in line with theories on stochastic resonance in the context of neuronal populations, which suggest that endogenous or exogenous noise can increase the sensitivity of neuronal populations to incoming signals.