Vision egg: an open-source library for realtime visual stimulus generation

Peak occipital alpha frequency mediates the relationship between sporting expertise and multiple object tracking performance

BACKGROUND

Multiple object tracking (MOT) is often used as a lab-based paradigm for investigating goal-driven attention as an indicator for "real-world" attention in tasks such as sport. When exploring MOT performance in the context of sporting expertise, we typically observe that individuals with sporting expertise outperform non-sporting individuals. There are a number of general explanations for performance differences such as cognitive transfer effects; however, the potential neurophysiological mechanisms explaining the relationship between sporting expertise and performance differences in MOT are not clear. Based on the role occipital alpha (posterior oscillations usually around 8-12 Hz) has been shown to have in visuospatial attention, the aim of this study was to examine whether individual differences in occipital peak alpha frequency (PAF) mediate the relationship between sporting expertise and performance in two object tracking tasks: a standard MOT task and a visuomotor-controlled object tracking task (multiple object avoidance [MOA]).

METHOD

Using electroencephalography (EEG), participants, who either played sport competitively or did not, had their posterior PAF measured at rest (eyes closed) across a 2-min window. They completed the two tasks separately from the resting EEG measures.

RESULTS

Those who engaged in sport performed better in the MOT and MOA tasks and had higher PAF. Higher PAF predicted superior MOT performance. The mediation analysis revealed that sporting individuals had significantly higher PAF, and this was in turn related to superior MOT performance.

CONCLUSIONS

It is suggested that PAF is a possible neurophysiological mediating mechanism as to why sporting individuals have superior MOT performance. There was no evidence that PAF mediated the relationship between sporting expertise and visuomotor MOA performance. Explanations and implications are discussed, and unanswered questions are proposed.

A synaptic corollary discharge signal suppresses midbrain visual processing during saccade-like locomotion

In motor control, the brain not only sends motor commands to the periphery, but also generates concurrent internal signals known as corollary discharge (CD) that influence sensory information processing around the time of movement. CD signals are important for identifying sensory input arising from self-motion and to compensate for it, but the underlying mechanisms remain unclear. Using whole-cell patch clamp recordings from neurons in the zebrafish optic tectum, we discovered an inhibitory synaptic signal, temporally locked to spontaneous and visually driven locomotion. This motor-related inhibition was appropriately timed to counteract visually driven excitatory input arising from the fish's own motion, and transiently suppressed tectal spiking activity. High-resolution calcium imaging revealed localized motor-related signals in the tectal neuropil and the upstream torus longitudinalis, suggesting that CD enters the tectum via this pathway. Together, our results show how visual processing is suppressed during self-motion by motor-related phasic inhibition. This may help explain perceptual saccadic suppression observed in many species.

Nonhuman primates exploit the prior assumption that the visual world is vertical

When human subjects tilt their heads in dark surroundings, the noisiness of vestibular information impedes precise reports on objects' orientation with respect to Earth's vertical axis. This difficulty is mitigated if a vertical visual background is available. Tilted visual backgrounds induce feelings of head tilt in subjects who are in fact upright. This is often explained as a result of the brain resorting to the prior assumption that natural visual backgrounds are vertical. Here, we tested whether monkeys show comparable perceptual mechanisms. To this end we trained two monkeys to align a visual arrow to a vertical reference line that had variable luminance across trials, while including a large, clearly visible background square whose orientation changed from trial to trial. On ∼20% of all trials, the vertical reference line was left out to measure the subjective visual vertical (SVV). When the frame was upright, the monkeys' SVV was aligned with the gravitational vertical. In accordance with the perceptual reports of humans, however, when the frame was tilted it induced an illusion of head tilt as indicated by a bias in SVV toward the frame orientation. Thus all primates exploit the prior assumption that the visual world is vertical.NEW & NOTEWORTHY Here we show that the principles that characterize the human perception of the vertical are shared by another old world primate species, the rhesus monkey, suggesting phylogenetic continuity. In both species the integration of visual and vestibular information on the orientation of the head relative to the world is similarly constrained by the prior assumption that the visual world is vertical in the sense of having an orientation that is congruent with the gravity vector.

A Robust Visual System for Looming Cue Detection Against Translating Motion

Collision detection is critical for autonomous vehicles or robots to serve human society safely. Detecting looming objects robustly and timely plays an important role in collision avoidance systems. The locust lobula giant movement detector (LGMD1) is specifically selective to looming objects which are on a direct collision course. However, the existing LGMD1 models cannot distinguish a looming object from a near and fast translatory moving object, because the latter can evoke a large amount of excitation that can lead to false LGMD1 spikes. This article presents a new visual neural system model (LGMD1) that applies a neural competition mechanism within a framework of separated ON and OFF pathways to shut off the translating response. The competition-based approach responds vigorously to monotonous ON/OFF responses resulting from a looming object. However, it does not respond to paired ON-OFF responses that result from a translating object, thereby enhancing collision selectivity. Moreover, a complementary denoising mechanism ensures reliable collision detection. To verify the effectiveness of the model, we have conducted systematic comparative experiments on synthetic and real datasets. The results show that our method exhibits more accurate discrimination between looming and translational events-the looming motion can be correctly detected. It also demonstrates that the proposed model is more robust than comparative models.

Attention and Prediction-Guided Motion Detection for Low-Contrast Small Moving Targets

Small target motion detection within complex natural environments is an extremely challenging task for autonomous robots. Surprisingly, the visual systems of insects have evolved to be highly efficient in detecting mates and tracking prey, even though targets occupy as small as a few degrees of their visual fields. The excellent sensitivity to small target motion relies on a class of specialized neurons, called small target motion detectors (STMDs). However, existing STMD-based models are heavily dependent on visual contrast and perform poorly in complex natural environments, where small targets generally exhibit extremely low contrast against neighboring backgrounds. In this article, we develop an attention-and-prediction-guided visual system to overcome this limitation. The developed visual system comprises three main subsystems, namely: 1) an attention module; 2) an STMD-based neural network; and 3) a prediction module. The attention module searches for potential small targets in the predicted areas of the input image and enhances their contrast against a complex background. The STMD-based neural network receives the contrast-enhanced image and discriminates small moving targets from background false positives. The prediction module foresees future positions of the detected targets and generates a prediction map for the attention module. The three subsystems are connected in a recurrent architecture, allowing information to be processed sequentially to activate specific areas for small target detection. Extensive experiments on synthetic and real-world datasets demonstrate the effectiveness and superiority of the proposed visual system for detecting small, low-contrast moving targets against complex natural environments.

jsQuestPlus: A JavaScript implementation of the QUEST+ method for estimating psychometric function parameters in online experiments

The two Bayesian adaptive psychometric methods named QUEST (Watson & Pelli, 1983) and QUEST+ (Watson, 2017) are widely used to estimate psychometric parameters, especially the threshold, in laboratory-based psychophysical experiments. Considering the increase of online psychophysical experiments in recent years, there is a growing need to have the QUEST and QUEST+ methods available online as well. We developed JavaScript libraries for both, with this article introducing one of them: jsQuestPlus. We offer integrations with online experimental tools such as jsPsych (de Leeuw, 2015), PsychoPy/JS (Peirce et al., 2019), and lab.js (Henninger et al., 2021). We measured the computation time required by jsQuestPlus under four conditions. Our simulations on 37 browser-computer combinations showed that the mean initialization time was 461.08 ms, 95% CI [328.29, 593.87], the mean computation time required to determine the stimulus parameters for the next trial was less than 1 ms, and the mean update time was 79.39 ms, 95% CI [46.22, 112.55] even in extremely demanding conditions. Additionally, psychometric parameters were estimated as accurately as the original QUEST+ method did. We conclude that jsQuestPlus is fast and accurate enough to conduct online psychophysical experiments despite the complexity of the matrix calculations. The latest version of jsQuestPlus can be downloaded freely from https://github.com/kurokida/jsQuestPlus under the MIT license.

A Time-Delay Feedback Neural Network for Discriminating Small, Fast-Moving Targets in Complex Dynamic Environments

Discriminating small moving objects within complex visual environments is a significant challenge for autonomous micro-robots that are generally limited in computational power. By exploiting their highly evolved visual systems, flying insects can effectively detect mates and track prey during rapid pursuits, even though the small targets equate to only a few pixels in their visual field. The high degree of sensitivity to small target movement is supported by a class of specialized neurons called small target motion detectors (STMDs). Existing STMD-based computational models normally comprise four sequentially arranged neural layers interconnected via feedforward loops to extract information on small target motion from raw visual inputs. However, feedback, another important regulatory circuit for motion perception, has not been investigated in the STMD pathway and its functional roles for small target motion detection are not clear. In this article, we propose an STMD-based neural network with feedback connection (feedback STMD), where the network output is temporally delayed, then fed back to the lower layers to mediate neural responses. We compare the properties of the model with and without the time-delay feedback loop and find that it shows a preference for high-velocity objects. Extensive experiments suggest that the feedback STMD achieves superior detection performance for fast-moving small targets, while significantly suppressing background false positive movements which display lower velocities. The proposed feedback model provides an effective solution in robotic visual systems for detecting fast-moving small targets that are always salient and potentially threatening.

Predicting Identity-Preserving Object Transformations in Human Posterior Parietal Cortex and Convolutional Neural Networks

Previous research shows that, within human occipito-temporal cortex (OTC), we can use a general linear mapping function to link visual object responses across nonidentity feature changes, including Euclidean features (e.g., position and size) and non-Euclidean features (e.g., image statistics and spatial frequency). Although the learned mapping is capable of predicting responses of objects not included in training, these predictions are better for categories included than those not included in training. These findings demonstrate a near-orthogonal representation of object identity and nonidentity features throughout human OTC. Here, we extended these findings to examine the mapping across both Euclidean and non-Euclidean feature changes in human posterior parietal cortex (PPC), including functionally defined regions in inferior and superior intraparietal sulcus. We additionally examined responses in five convolutional neural networks (CNNs) pretrained with object classification, as CNNs are considered as the current best model of the primate ventral visual system. We separately compared results from PPC and CNNs with those of OTC. We found that a linear mapping function could successfully link object responses in different states of nonidentity transformations in human PPC and CNNs for both Euclidean and non-Euclidean features. Overall, we found that object identity and nonidentity features are represented in a near-orthogonal, rather than complete-orthogonal, manner in PPC and CNNs, just like they do in OTC. Meanwhile, some differences existed among OTC, PPC, and CNNs. These results demonstrate the similarities and differences in how visual object information across an identity-preserving image transformation may be represented in OTC, PPC, and CNNs.

Mathematical study of neural feedback roles in small target motion detection

Building an efficient and reliable small target motion detection visual system is challenging for artificial intelligence robotics because a small target only occupies few pixels and hardly displays visual features in images. Biological visual systems that have evolved over millions of years could be ideal templates for designing artificial visual systems. Insects benefit from a class of specialized neurons, called small target motion detectors (STMDs), which endow them with an excellent ability to detect small moving targets against a cluttered dynamic environment. Some bio-inspired models featured in feed-forward information processing architectures have been proposed to imitate the functions of the STMD neurons. However, feedback, a crucial mechanism for visual system regulation, has not been investigated deeply in the STMD-based neural circuits and its roles in small target motion detection remain unclear. In this paper, we propose a time-delay feedback STMD model for small target motion detection in complex backgrounds. The main contributions of this study are as follows. First, a feedback pathway is designed by transmitting information from output-layer neurons to lower-layer interneurons in the STMD pathway and the role of the feedback is analyzed from the view of mathematical analysis. Second, to estimate the feedback constant, the existence and uniqueness of solutions for nonlinear dynamical systems formed by feedback loop are analyzed via Schauder's fixed point theorem and contraction mapping theorem. Finally, an iterative algorithm is designed to solve the nonlinear problem and the performance of the proposed model is tested by experiments. Experimental results demonstrate that the feedback is able to weaken background false positives while maintaining a minor effect on small targets. It outperforms existing STMD-based models regarding the accuracy of fast-moving small target detection in visual clutter. The proposed feedback approach could inspire the relevant modeling of robust motion perception robotics visual systems.

Impact of walking speed and motion adaptation on optokinetic nystagmus-like head movements in the blowfly Calliphora

The optokinetic nystagmus is a gaze-stabilizing mechanism reducing motion blur by rapid eye rotations against the direction of visual motion, followed by slower syndirectional eye movements minimizing retinal slip speed. Flies control their gaze through head turns controlled by neck motor neurons receiving input directly, or via descending neurons, from well-characterized directional-selective interneurons sensitive to visual wide-field motion. Locomotion increases the gain and speed sensitivity of these interneurons, while visual motion adaptation in walking animals has the opposite effects. To find out whether flies perform an optokinetic nystagmus, and how it may be affected by locomotion and visual motion adaptation, we recorded head movements of blowflies on a trackball stimulated by progressive and rotational visual motion. Flies flexibly responded to rotational stimuli with optokinetic nystagmus-like head movements, independent of their locomotor state. The temporal frequency tuning of these movements, though matching that of the upstream directional-selective interneurons, was only mildly modulated by walking speed or visual motion adaptation. Our results suggest flies flexibly control their gaze to compensate for rotational wide-field motion by a mechanism similar to an optokinetic nystagmus. Surprisingly, the mechanism is less state-dependent than the response properties of directional-selective interneurons providing input to the neck motor system.

Posterior parietal cortex predicts upcoming movement in dynamic sensorimotor control

SignificanceMost studies in sensorimotor neurophysiology have utilized reactive movements to stationary goals pre-defined by sensory cues, but this approach is fundamentally incapable of determining whether the observed neural activity reflects current sensory stimuli or predicts future movements. In the present study, we recorded single-neuron activity from behaving monkeys engaged in a dynamic, flexible, stimulus-response contingency task that enabled us to distinguish activity co-varying with sensory inflow from that co-varying with motor outflow in the posterior parietal cortex.

Predicting Identity-Preserving Object Transformations across the Human Ventral Visual Stream

In everyday life, we have no trouble categorizing objects varying in position, size, and orientation. Previous fMRI research shows that higher-level object processing regions in the human lateral occipital cortex may link object responses from different affine states (i.e., size and viewpoint) through a general linear mapping function capable of predicting responses to novel objects. In this study, we extended this approach to examine the mapping for both Euclidean (e.g., position and size) and non-Euclidean (e.g., image statistics and spatial frequency) transformations across the human ventral visual processing hierarchy, including areas V1, V2, V3, V4, ventral occipitotemporal cortex, and lateral occipitotemporal cortex. The predicted pattern generated from a linear mapping function could capture a significant amount of the changes associated with the transformations throughout the ventral visual stream. The derived linear mapping functions were not category independent as performance was better for the categories included than those not included in training and better between two similar versus two dissimilar categories in both lower and higher visual regions. Consistent with object representations being stronger in higher than in lower visual regions, pattern selectivity and object category representational structure were somewhat better preserved in the predicted patterns in higher than in lower visual regions. There were no notable differences between Euclidean and non-Euclidean transformations. These findings demonstrate a near-orthogonal representation of object identity and these nonidentity features throughout the human ventral visual processing pathway with these nonidentity features largely untangled from the identity features early in visual processing.SIGNIFICANCE STATEMENT Presently we still do not fully understand how object identity and nonidentity (e.g., position, size) information are simultaneously represented in the primate ventral visual system to form invariant representations. Previous work suggests that the human lateral occipital cortex may be linking different affine states of object representations through general linear mapping functions. Here, we show that across the entire human ventral processing pathway, we could link object responses in different states of nonidentity transformations through linear mapping functions for both Euclidean and non-Euclidean transformations. These mapping functions are not identity independent, suggesting that object identity and nonidentity features are represented in a near rather than a completely orthogonal manner.

Visual Disfunction due to the Selective Effect of Glutamate Agonists on Retinal Cells

One of the causes of nervous system degeneration is an excess of glutamate released upon several diseases. Glutamate analogs, like N-methyl-DL-aspartate (NMDA) and kainic acid (KA), have been shown to induce experimental retinal neurotoxicity. Previous results have shown that NMDA/KA neurotoxicity induces significant changes in the full field electroretinogram response, a thinning on the inner retinal layers, and retinal ganglion cell death. However, not all types of retinal neurons experience the same degree of injury in response to the excitotoxic stimulus. The goal of the present work is to address the effect of intraocular injection of different doses of NMDA/KA on the structure and function of several types of retinal cells and their functionality. To globally analyze the effect of glutamate receptor activation in the retina after the intraocular injection of excitotoxic agents, a combination of histological, electrophysiological, and functional tools has been employed to assess the changes in the retinal structure and function. Retinal excitotoxicity caused by the intraocular injection of a mixture of NMDA/KA causes a harmful effect characterized by a great loss of bipolar, amacrine, and retinal ganglion cells, as well as the degeneration of the inner retina. This process leads to a loss of retinal cell functionality characterized by an impairment of light sensitivity and visual acuity, with a strong effect on the retinal OFF pathway. The structural and functional injury suffered by the retina suggests the importance of the glutamate receptors expressed by different types of retinal cells. The effect of glutamate agonists on the OFF pathway represents one of the main findings of the study, as the evaluation of the retinal lesions caused by excitotoxicity could be specifically explored using tests that evaluate the OFF pathway.

A conserved role for sleep in supporting Spatial Learning in Drosophila

Sleep loss and aging impair hippocampus-dependent Spatial Learning in mammalian systems. Here we use the fly Drosophila melanogaster to investigate the relationship between sleep and Spatial Learning in healthy and impaired flies. The Spatial Learning assay is modeled after the Morris Water Maze. The assay uses a "thermal maze" consisting of a 5 × 5 grid of Peltier plates maintained at 36-37°C and a visual panorama. The first trial begins when a single tile that is associated with a specific visual cue is cooled to 25°C. For subsequent trials, the cold tile is heated, the visual panorama is rotated and the flies must find the new cold tile by remembering its association with the visual cue. Significant learning was observed with two different wild-type strains-Cs and 2U, validating our design. Sleep deprivation prior to training impaired Spatial Learning. Learning was also impaired in the classic learning mutant rutabaga (rut); enhancing sleep restored learning to rut mutants. Further, we found that flies exhibited a dramatic age-dependent cognitive decline in Spatial Learning starting at 20-24 days of age. These impairments could be reversed by enhancing sleep. Finally, we find that Spatial Learning requires dopaminergic signaling and that enhancing dopaminergic signaling in aged flies restored learning. Our results are consistent with the impairments seen in rodents and humans. These results thus demonstrate a critical conserved role for sleep in supporting Spatial Learning, and suggest potential avenues for therapeutic intervention during aging.

Validation of SATURN, a free, electronic, self-administered cognitive screening test

BACKGROUND

Cognitive screening is limited by clinician time and variability in administration and scoring. We therefore developed Self-Administered Tasks Uncovering Risk of Neurodegeneration (SATURN), a free, public-domain, self-administered, and automatically scored cognitive screening test, and validated it on inexpensive (<$100) computer tablets.

METHODS

SATURN is a 30-point test including orientation, word recall, and math items adapted from the Saint Louis University Mental Status test, modified versions of the Stroop and Trails tasks, and other assessments of visuospatial function and memory. English-speaking neurology clinic patients and their partners 50 to 89 years of age were given SATURN, the Montreal Cognitive Assessment (MoCA), and a brief survey about test preferences. For patients recruited from dementia clinics (n = 23), clinical status was quantified with the Clinical Dementia Rating (CDR) scale. Care partners (n = 37) were assigned CDR = 0.

RESULTS

SATURN and MoCA scores were highly correlated (P < .00001; r = 0.90). CDR sum-of-boxes scores were well-correlated with both tests (P < .00001) (r = -0.83 and -0.86, respectively). Statistically, neither test was superior. Most participants (83%) reported that SATURN was easy to use, and most either preferred SATURN over the MoCA (47%) or had no preference (32%).

DISCUSSION

Performance on SATURN-a fully self-administered and freely available (https://doi.org/10.5061/dryad.02v6wwpzr) cognitive screening test-is well-correlated with MoCA and CDR scores.

Functional, molecular and morphological heterogeneity of superficial interneurons in the larval zebrafish tectum

The superficial interneurons, SINs, of the zebrafish tectum, have been implicated in a range of visual functions, including size discrimination, directional selectivity, and looming-evoked escape. This raises the question if SIN subpopulations, despite their morphological similarities and shared anatomical position in the retinotectal processing stream, carry out diverse, task-specific functions in visual processing, or if they have simple tuning properties in common. Here we have further characterized the SINs through functional imaging, electrophysiological recordings, and neurotransmitter typing in two transgenic lines, the widely used Gal4s1156t and the recently reported LCRRH2-RH2-2:GFP. We found that about a third of the SINs strongly responded to changes in whole-field light levels, with a strong preference for OFF over ON stimuli. Interestingly, individual SINs were selectively tuned to a diverse range of narrow luminance decrements. Overall responses to whole-field luminance steps did not vary with the position of the SIN cell body along the depth of the tectal neuropil or with the orientation of its neurites. We ruled out the possibility that intrinsic photosensitivity of Gal4s1156t+ SINs contribute to the measured visual responses. We found that, while most SINs express GABAergic markers, a substantial minority express an excitatory neuronal marker, the vesicular glutamate transporter, expanding the possible roles of SIN function in the tectal circuitry. In conclusion, SINs represent a molecularly, morphologically, and functionally heterogeneous class of interneurons, with subpopulations that detect a range of specific visual features, to which we have now added narrow luminance decrements.

Oscillations in the central brain of Drosophila are phase locked to attended visual features

Object-based attention describes the brain's capacity to prioritize one set of stimuli while ignoring others. Human research suggests that the binding of diverse stimuli into one attended percept requires phase-locked oscillatory activity in the brain. Even insects display oscillatory brain activity during visual attention tasks, but it is unclear if neural oscillations in insects are selectively correlated to different features of attended objects. We addressed this question by recording local field potentials in the Drosophila central complex, a brain structure involved in visual navigation and decision making. We found that attention selectively increased the neural gain of visual features associated with attended objects and that attention could be redirected to unattended objects by activation of a reward circuit. Attention was associated with increased beta (20- to 30-Hz) oscillations that selectively locked onto temporal features of the attended visual objects. Our results suggest a conserved function for the beta frequency range in regulating selective attention to salient visual features.

The Cerebellum and Implicit Sequencing: Evidence from Cerebellar Ataxia

The cerebellum recognizes sequences from prior experiences and uses this information to generate internal models that predict future outcomes in a feedforward manner [Front Hum Neurosci 8: 475, 2014; Cortex 47: 137-44, 2011; Cerebellum 7: 611-5, 2008; J Neurosci 26: 9107-16, 2006]. This process has been well documented in the motor domain, but the cerebellum's role in cognitive sequencing, within the context of implicit versus explicit processes, is not well characterized. In this study, we tested individuals with cerebellar ataxia and healthy controls to clarify the role of the cerebellum sequencing using variations on implicit versus explicit and motor versus cognitive demands across five experiments. Converging results across these studies suggest that cerebellar feedforward mechanisms may be necessary for sequencing in the implicit domain only. In the ataxia group, rhythmic tapping, rate of motor learning, and implicit sequence learning were impaired. However, for cognitive sequencing that could be accomplished using explicit strategies, the cerebellar group performed normally, as though they shifted to extra-cerebellar mechanisms to compensate. For example, when cognitive and motor functions relied on cerebellar function simultaneously, the ataxia group's motor function was unaffected, in contrast to that of controls whose motor performance declined as a function of cognitive load. These findings indicated that the cerebellum is not critical for all forms of sequencing per se. Instead, it plays a fundamental role for sequencing within the implicit domain, whether functions are motor or cognitive. Moreover, individuals with cerebellar ataxia are generally able to compensate for cognitive sequencing when explicit strategies are available in order to preserve resources for motor function.

Modelling Drosophila motion vision pathways for decoding the direction of translating objects against cluttered moving backgrounds

Decoding the direction of translating objects in front of cluttered moving backgrounds, accurately and efficiently, is still a challenging problem. In nature, lightweight and low-powered flying insects apply motion vision to detect a moving target in highly variable environments during flight, which are excellent paradigms to learn motion perception strategies. This paper investigates the fruit fly Drosophila motion vision pathways and presents computational modelling based on cutting-edge physiological researches. The proposed visual system model features bio-plausible ON and OFF pathways, wide-field horizontal-sensitive (HS) and vertical-sensitive (VS) systems. The main contributions of this research are on two aspects: (1) the proposed model articulates the forming of both direction-selective and direction-opponent responses, revealed as principal features of motion perception neural circuits, in a feed-forward manner; (2) it also shows robust direction selectivity to translating objects in front of cluttered moving backgrounds, via the modelling of spatiotemporal dynamics including combination of motion pre-filtering mechanisms and ensembles of local correlators inside both the ON and OFF pathways, which works effectively to suppress irrelevant background motion or distractors, and to improve the dynamic response. Accordingly, the direction of translating objects is decoded as global responses of both the HS and VS systems with positive or negative output indicating preferred-direction or null-direction translation. The experiments have verified the effectiveness of the proposed neural system model, and demonstrated its responsive preference to faster-moving, higher-contrast and larger-size targets embedded in cluttered moving backgrounds.

Down-regulation of a cytokine secreted from peripheral fat bodies improves visual attention while reducing sleep in Drosophila

Sleep is vital for survival. Yet under environmentally challenging conditions, such as starvation, animals suppress their need for sleep. Interestingly, starvation-induced sleep loss does not evoke a subsequent sleep rebound. Little is known about how starvation-induced sleep deprivation differs from other types of sleep loss, or why some sleep functions become dispensable during starvation. Here, we demonstrate that down-regulation of the secreted cytokine unpaired 2 (upd2) in Drosophila flies may mimic a starved-like state. We used a genetic knockdown strategy to investigate the consequences of upd2 on visual attention and sleep in otherwise well-fed flies, thereby sidestepping the negative side effects of undernourishment. We find that knockdown of upd2 in the fat body (FB) is sufficient to suppress sleep and promote feeding-related behaviors while also improving selective visual attention. Furthermore, we show that this peripheral signal is integrated in the fly brain via insulin-expressing cells. Together, these findings identify a role for peripheral tissue-to-brain interactions in the simultaneous regulation of sleep quality and attention, to potentially promote adaptive behaviors necessary for survival in hungry animals.

The zebrafish visual system transmits dimming information via multiple segregated pathways

Vertebrate retinas contain circuits specialized to encode light level decrements. This information is transmitted to the brain by dimming-sensitive OFF retinal ganglion cells (OFF-RGCs) that respond to light decrements with increased firing. It is known that OFF-RGCs with distinct photosensitivity profiles form parallel visual channels to the vertebrate brain, yet how these channels are processed by first- and higher order brain areas has not been well characterized in any species. To address this question in the larval zebrafish visual system, we examined the visual response properties of a genetically identified population of tectal neurons with a defined axonal projection to a second-order visual area: id2b:gal4-positive torus longitudinalis projection neurons (TLPNs). TLPNs responded consistently to whole-field dimming stimuli and exhibited the strongest responses when dimming was preceded by low light levels. Functional characterization of OFF-RGC terminals in tectum revealed responses that varied in their photosensitivities: (a) low-sensitivity OFF-RGCs that selectively respond to large light decrements, (b) high-sensitivity OFF-RGCs that selectively encode small decrements, and (c) broad sensitivity OFF-RGCs that respond to a wide range of light decrements. Diverse photosensitivity profiles were also observed using pan-neuronal calcium imaging to identify dimming-responsive neurons in both tectum and torus longitudinalis. Together, these data support a model in which parallel OFF channels generated in the retina remain segregated across three stages of visual processing. Segregated OFF channels with different sensitivities may allow specific aspects of dimming-evoked behaviors to be modulated by ambient light levels.

Gradients of functional organization in posterior parietal cortex revealed by visual attention, visual short-term memory, and intrinsic functional connectivity

Visual attention and visual working memory tasks recruit a common network of lateral frontal cortical (LFC) and posterior parietal cortical (PPC) regions. Here, we examine finer-scale organization of this frontoparietal network. Three LFC regions recruited by visual cognition tasks, superior precentral sulcus (sPCS), inferior precentral sulcus (iPCS), and mid inferior frontal sulcus (midIFS) exhibit differential patterns of resting-state functional connectivity to PPC. A broad dorsomedial to ventrolateral gradient is observed, with sPCS connectivity dominating in the dorsomedial PPC band, iPCS dominating in the middle band, and midIFS dominating in the ventrolateral band. These connectivity-defined subregions of PPC capture differential task activation between a pair of visual attention and working memory tasks. The relative functional connectivity of sPCS and iPCS also varies along the rostral-caudal axis of the retinotopic regions of PPC. iPCS connectivity is relatively stronger near the IPS0/IPS1 and IPS2/IPS3 borders, especially on the lateral portions of these borders, which each preferentially encode central visual field representations. In contrast, sPCS connectivity is relatively stronger elsewhere in retinotopic IPS regions which preferentially encode peripheral visual field representations. These findings reveal fine-scale gradients in functional connectivity within the frontoparietal visual network that capture a high-degree of specificity in PPC functional organization.

A Directionally Selective Small Target Motion Detecting Visual Neural Network in Cluttered Backgrounds

Discriminating targets moving against a cluttered background is a huge challenge, let alone detecting a target as small as one or a few pixels and tracking it in flight. In the insect's visual system, a class of specific neurons, called small target motion detectors (STMDs), have been identified as showing exquisite selectivity for small target motion. Some of the STMDs have also demonstrated direction selectivity which means these STMDs respond strongly only to their preferred motion direction. Direction selectivity is an important property of these STMD neurons which could contribute to tracking small targets such as mates in flight. However, little has been done on systematically modeling these directionally selective STMD neurons. In this paper, we propose a directionally selective STMD-based neural network for small target detection in a cluttered background. In the proposed neural network, a new correlation mechanism is introduced for direction selectivity via correlating signals relayed from two pixels. Then, a lateral inhibition mechanism is implemented on the spatial field for size selectivity of the STMD neurons. Finally, a population vector algorithm is used to encode motion direction of small targets. Extensive experiments showed that the proposed neural network not only is in accord with current biological findings, i.e., showing directional preferences but also worked reliably in detecting the small targets against cluttered backgrounds.

A Robust Visual System for Small Target Motion Detection Against Cluttered Moving Backgrounds

Monitoring small objects against cluttered moving backgrounds is a huge challenge to future robotic vision systems. As a source of inspiration, insects are quite apt at searching for mates and tracking prey, which always appear as small dim speckles in the visual field. The exquisite sensitivity of insects for small target motion, as revealed recently, is coming from a class of specific neurons called small target motion detectors (STMDs). Although a few STMD-based models have been proposed, these existing models only use motion information for small target detection and cannot discriminate small targets from small-target-like background features (named fake features). To address this problem, this paper proposes a novel visual system model (STMD+) for small target motion detection, which is composed of four subsystems-ommatidia, motion pathway, contrast pathway, and mushroom body. Compared with the existing STMD-based models, the additional contrast pathway extracts directional contrast from luminance signals to eliminate false positive background motion. The directional contrast and the extracted motion information by the motion pathway are integrated into the mushroom body for small target discrimination. Extensive experiments showed the significant and consistent improvements of the proposed visual system model over the existing STMD-based models against fake features.

Ratcave: A 3D graphics python package for cognitive psychology experiments

We present here a free, open source Python 3D graphics library called Ratcave that extends existing Python psychology stimulus software by allowing scientists to load, display, and transform 3D stimuli created in 3D modeling software. This library makes 3D programming intuitive to new users by providing 3D graphics engine concepts (Mesh, Scene, Light, and Camera classes) that can be manipulated using an interface similar to existing 2D stimulus libraries. In addition, the use of modern OpenGL constructs by Ratcave helps scientists create fast, hardware-accelerated dynamic stimuli using the same intuitive high-level, lightweight interface. Because Ratcave supplements, rather than replaces, existing Python stimulus libraries, scientists can continue to use their preferred libraries by simply adding Ratcave graphics to their existing experiments. We hope this tool will be useful both as a stimulus library and as an example of how tightly-focused libraries can add quality to the existing scientific open-source software ecosystem.

Visual spatial attention and spatial working memory do not draw on shared capacity-limited core processes

The extent to which similar capacity limits in visual attention and visual working memory indicate a common shared underlying mechanism is currently still debated. In the spatial domain, the multiple object tracking (MOT) task has been used to assess the relationship between spatial attention and spatial working memory though existing results have been inconclusive. In three dual task experiments, we examined the extent of interference between attention to spatial positions and memory for spatial positions. When the position monitoring task required keeping track of target identities through colour-location binding, we found a moderate detrimental effect of position monitoring on spatial working memory and an ambiguous interaction effect. However, when this task requirement was removed, load increases in neither task were detrimental to the other. The only very moderate interference effect that remained resided in an interaction between load types but was not consistent with shared capacity between tasks-rather it was consistent with content-related crosstalk between spatial representations. Contrary to propositions that spatial attention and spatial working memory may draw on a common shared set of core processes, these findings indicate that for a purely spatial task, perceptual attention and working memory appear to recruit separate core capacity-limited processes.

Drosulfakinin signaling in fruitless circuitry antagonizes P1 neurons to regulate sexual arousal in Drosophila

Animals perform or terminate particular behaviors by integrating external cues and internal states through neural circuits. Identifying neural substrates and their molecular modulators promoting or inhibiting animal behaviors are key steps to understand how neural circuits control behaviors. Here, we identify the Cholecystokinin-like peptide Drosulfakinin (DSK) that functions at single-neuron resolution to suppress male sexual behavior in Drosophila. We found that Dsk neurons physiologically interact with male-specific P1 neurons, part of a command center for male sexual behaviors, and function oppositely to regulate multiple arousal-related behaviors including sex, sleep and spontaneous walking. We further found that the DSK-2 peptide functions through its receptor CCKLR-17D3 to suppress sexual behaviors in flies. Such a neuropeptide circuit largely overlaps with the fruitless-expressing neural circuit that governs most aspects of male sexual behaviors. Thus DSK/CCKLR signaling in the sex circuitry functions antagonistically with P1 neurons to balance arousal levels and modulate sexual behaviors.

Task modulation of the 2-pathway characterization of occipitotemporal and posterior parietal visual object representations

Recent studies have reported the existence of rich non-spatial visual object representations in both human and monkey posterior parietal cortex (PPC), similar to those found in occipito-temporal cortex (OTC). Despite this similarity, we recently showed that visual object representation still differ between OTC and PPC in two aspects. In one study, by manipulating whether object shape or color was task relevant, we showed that visual object representations were under greater top-down attention and task control in PPC than in OTC (Vaziri-Pashkam & Xu, 2017, J Neurosci). In another study, using a bottom-up data driven approach, we showed that there exists a large separation between PPC and OTC regions in the representational space, with OTC regions lining up hierarchically along an OTC pathway and PPC regions lining up hierarchically along an orthogonal PPC pathway (Vaziri-Pashkam & Xu, 2019, Cereb Cortex). To understand the interaction of goal-driven visual processing and the two-pathway structure in the representational space, here we performed a set of new analyses of the data from the three experiments of Vaziri-Pashkam and Xu (2017) and directly compared the two-pathway separation of OTC and PPC regions when object shapes were attended and task relevant and when they were not. We found that in all three experiments the correlation of visual object representational structure between superior IPS (a key PPC visual region) and lateral and ventral occipito-temporal regions (higher OTC visual regions) became greater when object shapes were attended than when they were not. This modified the two-pathway structure, with PPC regions moving closer to higher OTC regions and a compression of the PPC pathway towards the OTC pathway in the representational space when shapes were attended. Consistent with this observation, the correlation between neural and behavioral measures of visual representational structure was also higher in superior IPS when shapes were attended than when they were not. By comparing representational structures across experiments and tasks, we further showed that attention to object shape resulted in the formation of more similar object representations in superior IPS across experiments than between the two tasks within the same experiment despite noise and stimulus differences across the experiments. Overall, these results demonstrated that, despite the separation of the OTC and PPC pathways in the representational space, the visual representational structure of PPC is flexible and can be modulated by the task demand. This reaffirms the adaptive nature of visual processing in PPC and further distinguishes it from the more invariant nature of visual processing in OTC.

PyParadigm-A Python Library to Build Screens in a Declarative Way

In experimental psychology, subjects are often confronted with computer-based experimental paradigms. Creating such paradigms can require a lot of effort. PyParadigm is a newly developed Python library to ease the development of such paradigms by employing a declarative approach to build user interfaces (UIs). Paradigm specifications in this approach requires much less code and training than in alternative libraries. Although PyParadigm was initially developed for the creation of experimental paradigms, it is generally suited to build UIs that display or interact with 2D objects.

PsychoPy2: Experiments in behavior made easy

PsychoPy is an application for the creation of experiments in behavioral science (psychology, neuroscience, linguistics, etc.) with precise spatial control and timing of stimuli. It now provides a choice of interface; users can write scripts in Python if they choose, while those who prefer to construct experiments graphically can use the new Builder interface. Here we describe the features that have been added over the last 10 years of its development. The most notable addition has been that Builder interface, allowing users to create studies with minimal or no programming, while also allowing the insertion of Python code for maximal flexibility. We also present some of the other new features, including further stimulus options, asynchronous time-stamped hardware polling, and better support for open science and reproducibility. Tens of thousands of users now launch PsychoPy every month, and more than 90 people have contributed to the code. We discuss the current state of the project, as well as plans for the future.

Visual experience drives sleep need in Drosophila

Sleep optimizes waking behavior, however, waking experience may also influence sleep. We used the fruit fly Drosophila melanogaster to investigate the relationship between visual experience and sleep in wild-type and mutant flies. We found that the classical visual mutant, optomotor-blind (omb), which has undeveloped horizontal system/vertical system (HS/VS) motion-processing cells and are defective in motion and visual salience perception, showed dramatically reduced and less consolidated sleep compared to wild-type flies. In contrast, optogenetic activation of the HS/VS motion-processing neurons in wild-type flies led to an increase in sleep following the activation, suggesting an increase in sleep pressure. Surprisingly, exposing wild-type flies to repetitive motion stimuli for extended periods did not increase sleep pressure. However, we observed that exposing flies to more complex image sequences from a movie led to more consolidated sleep, particularly when images were randomly shuffled through time. Our results suggest that specific forms of visual experience that involve motion circuits and complex, nonrepetitive imagery, drive sleep need in Drosophila.

The effects of psychiatric history and age on self-regulation of the default mode network

Real-time neurofeedback enables human subjects to learn to regulate their brain activity, effecting behavioral changes and improvements of psychiatric symptomatology. Neurofeedback up-regulation and down-regulation have been assumed to share common neural correlates. Neuropsychiatric pathology and aging incur suboptimal functioning of the default mode network. Despite the exponential increase in real-time neuroimaging studies, the effects of aging, pathology and the direction of regulation on neurofeedback performance remain largely unknown. Using real-time fMRI data shared through the Rockland Sample Real-Time Neurofeedback project (N = 136) and open-access analyses, we first modeled neurofeedback performance and learning in a group of subjects with psychiatric history (n_a = 74) and a healthy control group (n_b = 62). Subsequently, we examined the relationship between up-regulation and down-regulation learning, the relationship between age and neurofeedback performance in each group and differences in neurofeedback performance between the two groups. For interpretative purposes, we also investigated functional connectomics prior to neurofeedback. Results show that in an initial session of default mode network neurofeedback with real-time fMRI, up-regulation and down-regulation learning scores are negatively correlated. This finding is related to resting state differences in the eigenvector centrality of the posterior cingulate cortex. Moreover, age correlates negatively with default mode network neurofeedback performance, only in absence of psychiatric history. Finally, adults with psychiatric history outperform healthy controls in default mode network up-regulation. Interestingly, the performance difference is related to no up-regulation learning in controls. This finding is supported by marginally higher default mode network centrality during resting state, in the presence of psychiatric history.

An Information-Driven 2-Pathway Characterization of Occipitotemporal and Posterior Parietal Visual Object Representations

Recent studies have demonstrated the existence of rich visual representations in both occipitotemporal cortex (OTC) and posterior parietal cortex (PPC). Using fMRI decoding and a bottom-up data-driven approach, we showed that although robust object category representations exist in both OTC and PPC, there is an information-driven 2-pathway separation among these regions in the representational space, with occipitotemporal regions arranging hierarchically along 1 pathway and posterior parietal regions along another pathway. We obtained 10 independent replications of this 2-pathway distinction, accounting for 58-81% of the total variance of the region-wise differences in visual representation. The separation of the PPC regions from higher occipitotemporal regions was not driven by a difference in tolerance to changes in low-level visual features, did not rely on the presence of special object categories, and was present whether or not object category was task relevant. Our information-driven 2-pathway structure differs from the well-known ventral-what and dorsal-where/how characterization of posterior brain regions. Here both pathways contain rich nonspatial visual representations. The separation we see likely reflects a difference in neural coding scheme used by PPC to represent visual information compared with that of OTC.

Shady: A software engine for real-time visual stimulus manipulation

BACKGROUND

Precise definition, rendering and manipulation of visual stimuli are essential in neuroscience. Rather than implementing these tasks from scratch, scientists benefit greatly from using reusable software routines from freely available toolboxes. Existing toolboxes work well when the operating system and hardware are painstakingly optimized, but may be less suited to applications that require multi-tasking (for example, closed-loop systems that involve real-time acquisition and processing of signals).

NEW METHOD

We introduce a new cross-platform visual stimulus toolbox called Shady (https://pypi.org/project/Shady)-so called because of its heavy reliance on a shader program to perform parallel pixel processing on a computer's graphics processor. It was designed with an emphasis on performance robustness in multi-tasking applications under unforgiving conditions. For optimal timing performance, the CPU drawing management commands are carried out by a compiled binary engine. For configuring stimuli and controlling their changes over time, Shady provides a programmer's interface in Python, a powerful, accessible and widely-used high-level programming language.

RESULTS

Our timing benchmark results illustrate that Shady's hybrid compiled/interpreted architecture requires less time to complete drawing operations, exhibits smaller variability in frame-to-frame timing, and hence drops fewer frames, than pure-Python solutions under matched conditions of resource contention. This performance gain comes despite an expansion of functionality (e.g. "noisy-bit" dithering as standard on all pixels and all frames, to enhance effective dynamic range) relative to previous offerings.

CONCLUSIONS

Shady simultaneously advances the functionality and performance available to scientists for rendering visual stimuli and manipulating them in real time.

Sleep regulates visual selective attention in Drosophila

Although sleep deprivation is known to impair attention in humans and other mammals, the underlying reasons are not well understood, and whether similar effects are present in non-mammalian species is not known. We therefore sought to investigate whether sleep is important for optimizing attention in an invertebrate species, the genetic model Drosophila melanogaster We developed a high-throughput paradigm to measure visual attention in freely walking Drosophila, using competing foreground/background visual stimuli. We found that whereas sleep-deprived flies could respond normally to either stimulus alone, they were more distracted by background cues in a visual competition task. Other stressful manipulations such as starvation, heat exposure and mechanical stress had no effects on visual attention in this paradigm. In contrast to sleep deprivation, providing additional sleep using the GABA-A agonist 4,5,6,7-tetrahydroisoxazolo-[5,4-c]pyridine-3-ol (THIP) did not affect attention in wild-type flies, but specifically improved attention in the learning mutant dunce Our results reveal a key function of sleep in optimizing attention processes in Drosophila, and establish a behavioral paradigm that can be used to explore the molecular mechanisms involved.

Team ball sport participation is associated with performance in two sustained visual attention tasks: Position monitoring and target identification in rapid serial visual presentation streams

We investigated the relationship between participation in team ball sports and performance in two sustained spatiotemporal attention tasks-a position monitoring variant of the multiple object tracking (MOT) task and target identification in the rapid serial visual presentation (RSVP) task. Thirty participants were asked about the frequency of their participation in team ball sports and undertook both the MOT task and RSVP task. In the MOT task, participants viewed an array of eight discs as they moved unpredictably for 3-8s before disappearing. On each trial, a subset of these were marked as targets for tracking, meaning that participants attempted to keep track of their positions on the screen with as much precision as possible. At the end of each trial, participants reported the final perceived position of a queried target. In the RSVP task, a stream of letters was presented at the center of the screen and participants attempted to report either one or both of two target letters embedded in the stream. Participation in team ball sports was associated with superior performance in both tasks: in the MOT task, individuals reporting more time spent playing team ball sports on a weekly basis were able to report the positions of targets with greater precision, and in the RSVP task they reported targets more accurately. The current findings add to the literature of somewhat mixed findings regarding the extent to which participation in sports may be associated with superior visual attention abilities.

Spatial Frequency Tolerant Visual Object Representations in the Human Ventral and Dorsal Visual Processing Pathways

Primate ventral and dorsal visual pathways both contain visual object representations. Dorsal regions receive more input from magnocellular system while ventral regions receive inputs from both magnocellular and parvocellular systems. Due to potential differences in the spatial sensitivites of manocellular and parvocellular systems, object representations in ventral and dorsal regions may differ in how they represent visual input from different spatial scales. To test this prediction, we asked observers to view blocks of images from six object categories, shown in full spectrum, high spatial frequency (SF), or low SF. We found robust object category decoding in all SF conditions as well as SF decoding in nearly all the early visual, ventral, and dorsal regions examined. Cross-SF decoding further revealed that object category representations in all regions exhibited substantial tolerance across the SF components. No difference between ventral and dorsal regions was found in their preference for the different SF components. Further comparisons revealed that, whereas differences in the SF component separated object category representations in early visual areas, such a separation was much smaller in downstream ventral and dorsal regions. In those regions, variations among the object categories played a more significant role in shaping the visual representational structures. Our findings show that ventral and dorsal regions are similar in how they represent visual input from different spatial scales and argue against a dissociation of these regions based on differential sensitivity to different SFs.

Inhibitory Control Mediates the Association between Perceived Stress and Secure Relationship Quality

Past research has demonstrated negative associations between exposure to stressors and quality of interpersonal relationships among children and adolescents. Nevertheless, underlying mechanisms of this association remain unclear. Chronic stress has been shown to disrupt prefrontal functioning in the brain, including inhibitory control abilities, and evidence is accumulating that inhibitory control may play an important role in secure interpersonal relationship quality, including peer problems and social competence. In this prospective longitudinal study, we examine whether changes in inhibitory control, measured at both behavioral and neural levels, mediate the association between stress and changes in secure relationship quality with parents and peers. The sample included 167 adolescents (53% males) who were first recruited at age 13 or 14 years and assessed annually three times. Adolescents' inhibitory control was measured by their behavioral performance and brain activities, and adolescents self-reported perceived stress levels and relationship quality with mothers, fathers, and peers. Results suggest that behavioral inhibitory control mediates the association between perceived stress and adolescent's secure relationship quality with their mothers and fathers, but not their peers. In contrast, given that stress was not significantly correlated with neural inhibitory control, we did not further test the mediation path. Our results highlight the role of inhibitory control as a process through which stressful life experiences are related to impaired secure relationship quality between adolescents and their mothers and fathers.

Interactive Light Stimulus Generation with High Performance Real-Time Image Processing and Simple Scripting

Light stimulation with precise and complex spatial and temporal modulation is demanded by a series of research fields like visual neuroscience, optogenetics, ophthalmology, and visual psychophysics. We developed a user-friendly and flexible stimulus generating framework (GEARS GPU-based Eye And Retina Stimulation Software), which offers access to GPU computing power, and allows interactive modification of stimulus parameters during experiments. Furthermore, it has built-in support for driving external equipment, as well as for synchronization tasks, via USB ports. The use of GEARS does not require elaborate programming skills. The necessary scripting is visually aided by an intuitive interface, while the details of the underlying software and hardware components remain hidden. Internally, the software is a C++/Python hybrid using OpenGL graphics. Computations are performed on the GPU, and are defined in the GLSL shading language. However, all GPU settings, including the GPU shader programs, are automatically generated by GEARS. This is configured through a method encountered in game programming, which allows high flexibility: stimuli are straightforwardly composed using a broad library of basic components. Stimulus rendering is implemented solely in C++, therefore intermediary libraries for interfacing could be omitted. This enables the program to perform computationally demanding tasks like en-masse random number generation or real-time image processing by local and global operations.

Innate visual preferences and behavioral flexibility in Drosophila

Visual decision-making in animals is influenced by innate preferences as well as experience. Interaction between hard-wired responses and changing motivational states determines whether a visual stimulus is attractive, aversive, or neutral. It is however difficult to separate the relative contribution of nature versus nurture in experimental paradigms, especially for more complex visual parameters such as the shape of objects. We used a closed-loop virtual reality paradigm for walking Drosophila flies to uncover innate visual preferences for the shape and size of objects, in a recursive choice scenario allowing the flies to reveal their visual preferences over time. We found that Drosophila flies display a robust attraction / repulsion profile for a range of objects sizes in this paradigm, and that this visual preference profile remains evident under a variety of conditions and persists into old age. We also demonstrate a level of flexibility in this behavior: innate repulsion to certain objects could be transiently overridden if these were novel, although this effect was only evident in younger flies. Finally, we show that a neuromodulatory circuit in the fly brain, Drosophila neuropeptide F (dNPF), can be recruited to guide visual decision-making. Optogenetic activation of dNPF-expressing neurons converted a visually repulsive object into a more attractive object. This suggests that dNPF activity in the Drosophila brain guides ongoing visual choices, to override innate preferences and thereby provide a necessary level of behavioral flexibility in visual decision-making.

Eye-hand coordination during flexible manual interception of an abruptly appearing, moving target

As a vital skill in an evolving world, interception of moving objects relies on accurate prediction of target motion. In natural circumstances, active gaze shifts often accompany hand movements when exploring targets of interest, but how eye and hand movements are coordinated during manual interception and their dependence on visual prediction remain unclear. Here, we trained gaze-unrestrained monkeys to manually intercept targets appearing at random locations and circularly moving with random speeds. We found that well-trained animals were able to intercept the targets with adequate compensation for both sensory transmission and motor delays. Before interception, the animals' gaze followed the targets with adequate compensation for the sensory delay, but not for extra target displacement during the eye movements. Both hand and eye movements were modulated by target kinematics, and their reaction times were correlated. Moreover, retinal errors and reaching errors were correlated across different stages of reach execution. Our results reveal eye-hand coordination during manual interception, yet the eye and hand movements may show different levels of prediction based on the task context.

NEW & NOTEWORTHY Here we studied the eye-hand coordination of monkeys during flexible manual interception of a moving target. Eye movements were untrained and not explicitly associated with reward. We found that the initial saccades toward the moving target adequately compensated for sensory transmission delays, but not for extra target displacement, whereas the reaching arm movements fully compensated for sensorimotor delays, suggesting that the mode of eye-hand coordination strongly depends on behavioral context.

Scene content is predominantly conveyed by high spatial frequencies in scene-selective visual cortex

In complex real-world scenes, image content is conveyed by a large collection of intertwined visual features. The visual system disentangles these features in order to extract information about image content. Here, we investigate the role of one integral component: the content of spatial frequencies in an image. Specifically, we measure the amount of image content carried by low versus high spatial frequencies for the representation of real-world scenes in scene-selective regions of human visual cortex. To this end, we attempted to decode scene categories from the brain activity patterns of participants viewing scene images that contained the full spatial frequency spectrum, only low spatial frequencies, or only high spatial frequencies, all carefully controlled for contrast and luminance. Contrary to the findings from numerous behavioral studies and computational models that have highlighted how low spatial frequencies preferentially encode image content, decoding of scene categories from the scene-selective brain regions, including the parahippocampal place area (PPA), was significantly more accurate for high than low spatial frequency images. In fact, decoding accuracy was just as high for high spatial frequency images as for images containing the full spatial frequency spectrum in scene-selective areas PPA, RSC, OPA and object selective area LOC. We also found an interesting dissociation between the posterior and anterior subdivisions of PPA: categories were decodable from both high and low spatial frequency scenes in posterior PPA but only from high spatial frequency scenes in anterior PPA; and spatial frequency was explicitly decodable from posterior but not anterior PPA. Our results are consistent with recent findings that line drawings, which consist almost entirely of high spatial frequencies, elicit a neural representation of scene categories that is equivalent to that of full-spectrum color photographs. Collectively, these findings demonstrate the importance of high spatial frequencies for conveying the content of complex real-world scenes.

Selecting multiple features delays perception, but only when targets are horizontally arranged

Based on the finding that perception is lagged by attention split on multiple features (Lo et al., 2012), this study investigated how the feature-based lag effect interacts with the target spatial arrangement. Participants were presented with gratings the spatial frequencies of which constantly changed. The task was to monitor two gratings of the same or different colors and report their spatial frequencies right before the stimulus offset. The results showed a perceptual lag wherein the reported value was closer to the physical value some time prior to the stimulus offset. This lag effect was larger when the two gratings were of different colors than when they were the same color. Furthermore, the feature-based lag effect was statistically significant when the two gratings were horizontally arranged but not when they were vertically or diagonally arranged. A model is proposed to explain the effect of target arrangement: When targets are horizontally arranged, selecting an additional feature delays perception. When targets are vertically or diagonally arranged, target selection for the lower field is prioritized. This prioritization on the lower target might prompt observers to only select the lower target and ignore the upper one, and this causes more perceptual errors without delaying perception.

Goal-Directed Visual Processing Differentially Impacts Human Ventral and Dorsal Visual Representations

Recent studies have challenged the ventral/"what" and dorsal/"where" two-visual-processing-pathway view by showing the existence of "what" and "where" information in both pathways. Is the two-pathway distinction still valid? Here, we examined how goal-directed visual information processing may differentially impact visual representations in these two pathways. Using fMRI and multivariate pattern analysis, in three experiments on human participants (57% females), by manipulating whether color or shape was task-relevant and how they were conjoined, we examined shape-based object category decoding in occipitotemporal and parietal regions. We found that object category representations in all the regions examined were influenced by whether or not object shape was task-relevant. This task effect, however, tended to decrease as task-relevant and irrelevant features were more integrated, reflecting the well-known object-based feature encoding. Interestingly, task relevance played a relatively minor role in driving the representational structures of early visual and ventral object regions. They were driven predominantly by variations in object shapes. In contrast, the effect of task was much greater in dorsal than ventral regions, with object category and task relevance both contributing significantly to the representational structures of the dorsal regions. These results showed that, whereas visual representations in the ventral pathway are more invariant and reflect "what an object is," those in the dorsal pathway are more adaptive and reflect "what we do with it." Thus, despite the existence of "what" and "where" information in both visual processing pathways, the two pathways may still differ fundamentally in their roles in visual information representation.SIGNIFICANCE STATEMENT Visual information is thought to be processed in two distinctive pathways: the ventral pathway that processes "what" an object is and the dorsal pathway that processes "where" it is located. This view has been challenged by recent studies revealing the existence of "what" and "where" information in both pathways. Here, we found that goal-directed visual information processing differentially modulates shape-based object category representations in the two pathways. Whereas ventral representations are more invariant to the demand of the task, reflecting what an object is, dorsal representations are more adaptive, reflecting what we do with the object. Thus, despite the existence of "what" and "where" information in both pathways, visual representations may still differ fundamentally in the two pathways.

Functional Evidence for a Cerebellar Node of the Dorsal Attention Network

The "dorsal attention network" or "frontoparietal network" refers to a network of cortical regions that support sustained attention and working memory. Recent work has demonstrated that cortical nodes of the dorsal attention network possess intrinsic functional connections with a region in ventral cerebellum, in the vicinity of lobules VII/VIII. Here, we performed a series of task-based and resting-state fMRI experiments to investigate cerebellar participation in the dorsal attention network in humans. We observed that visual working memory and visual attention tasks robustly recruit cerebellar lobules VIIb and VIIIa, in addition to canonical cortical dorsal attention network regions. Across the cerebellum, resting-state functional connectivity with the cortical dorsal attention network strongly predicted the level of activation produced by attention and working memory tasks. Critically, cerebellar voxels that were most strongly connected with the dorsal attention network selectively exhibited load-dependent activity, a hallmark of the neural structures that support visual working memory. Finally, we examined intrinsic functional connectivity between task-responsive portions of cerebellar lobules VIIb/VIIIa and cortex. Cerebellum-to-cortex functional connectivity strongly predicted the pattern of cortical activation during task performance. Moreover, resting-state connectivity patterns revealed that cerebellar lobules VIIb/VIIIa group with cortical nodes of the dorsal attention network. This evidence leads us to conclude that the conceptualization of the dorsal attention network should be expanded to include cerebellar lobules VIIb/VIIIa.

SIGNIFICANCE STATEMENT

The functional participation of cerebellar structures in nonmotor cortical networks remains poorly understood and is highly understudied, despite the fact that the cerebellum possesses many more neurons than the cerebral cortex. Although visual attention paradigms have been reported to activate cerebellum, many researchers have largely dismissed the possibility of a cerebellar contribution to attention in favor of a motor explanation, namely, eye movements. The present study demonstrates that a cerebellar subdivision (mainly lobules VIIb/VIIIa), which exhibits strong intrinsic functional connectivity with the cortical dorsal attention network, also closely mirrors a myriad of cortical dorsal attention network responses to visual attention and working memory tasks. This evidence strongly supports a reconceptualization of the dorsal attention network to include cerebellar lobules VIIb/VIIIa.

Complex object motion represented by context-dependent correlated activity of visual interneurones

Accurate and adaptive encoding of complex, dynamic visual information is critical for the survival of many animals. Studies across a range of taxa have investigated behavioral and neuronal responses to objects that represent a threat, such as a looming object approaching along a direct collision course. By investigating neural mechanisms of avoidance behaviors through recording multineuronal activity, it is possible to better understand how complex visual information is represented in circuits that ultimately drive behaviors. We used multichannel electrodes to record from the well-studied locust nervous system to explore how object motion is reflected in activity of correlated neural activity. We presented locusts (Locusta migratoria) with objects that moved along one of 11 unique trajectories and recorded from descending interneurons within the ventral nerve cord. Spike sorting resulted in 405 discriminated units across 20 locusts and we found that 75% of the units responded to some form of object motion. Dimensionality reduction through principal component (PCA) and dynamic factor (DFA) analyses revealed population vector responses within individuals and common firing trends across the pool of discriminated units, respectively. Population vector composition (PCA) varied with the stimulus and common trends (DFA) showed unique tuning related to changes in the visual size and trajectory of the object through time. These findings demonstrate that this well-described collision detection system is more complex than previously envisioned and will drive future experiments to explore fundamental principles of how visual information is processed through context-dependent dynamic ensembles of neurons to initiate and control complex behavior.

A sublethal dose of a neonicotinoid insecticide disrupts visual processing and collision avoidance behaviour in Locusta migratoria

Neonicotinoids are known to affect insect navigation and vision, however the mechanisms of these effects are not fully understood. A visual motion sensitive neuron in the locust, the Descending Contralateral Movement Detector (DCMD), integrates visual information and is involved in eliciting escape behaviours. The DCMD receives coded input from the compound eyes and monosynaptically excites motorneurons involved in flight and jumping. We show that imidacloprid (IMD) impairs neural responses to visual stimuli at sublethal concentrations, and these effects are sustained two and twenty-four hours after treatment. Most significantly, IMD disrupted bursting, a coding property important for motion detection. Specifically, IMD reduced the DCMD peak firing rate within bursts at ecologically relevant doses of 10 ng/g (ng IMD per g locust body weight). Effects on DCMD firing translate to deficits in collision avoidance behaviours: exposure to 10 ng/g IMD attenuates escape manoeuvers while 100 ng/g IMD prevents the ability to fly and walk. We show that, at ecologically-relevant doses, IMD causes significant and lasting impairment of an important pathway involved with visual sensory coding and escape behaviours. These results show, for the first time, that a neonicotinoid pesticide directly impairs an important, taxonomically conserved, motion-sensitive visual network.

Transient Dysregulation of Dopamine Signaling in a Developing Drosophila Arousal Circuit Permanently Impairs Behavioral Responsiveness in Adults

The dopamine ontogeny hypothesis for schizophrenia proposes that transient dysregulation of the dopaminergic system during brain development increases the likelihood of this disorder in adulthood. To test this hypothesis in a high-throughput animal model, we have transiently manipulated dopamine signaling in the developing fruit fly Drosophila melanogaster and examined behavioral responsiveness in adult flies. We found that either a transient increase of dopamine neuron activity or a transient decrease of dopamine receptor expression during fly brain development permanently impairs behavioral responsiveness in adults. A screen for impaired responsiveness revealed sleep-promoting neurons in the central brain as likely postsynaptic dopamine targets modulating these behavioral effects. Transient dopamine receptor knockdown during development in a restricted set of ~20 sleep-promoting neurons recapitulated the dopamine ontogeny phenotype, by permanently reducing responsiveness in adult animals. This suggests that disorders involving impaired behavioral responsiveness might result from defective ontogeny of sleep/wake circuits.

The real-time fMRI neurofeedback based stratification of Default Network Regulation Neuroimaging data repository

This data descriptor describes a repository of openly shared data from an experiment to assess inter-individual differences in default mode network (DMN) activity. This repository includes cross-sectional functional magnetic resonance imaging (fMRI) data from the Multi Source Interference Task, to assess DMN deactivation, the Moral Dilemma Task, to assess DMN activation, a resting state fMRI scan, and a DMN neurofeedback paradigm, to assess DMN modulation, along with accompanying behavioral and cognitive measures. We report technical validation from n=125 participants of the final targeted sample of 180 participants. Each session includes acquisition of one whole-brain anatomical scan and whole-brain echo-planar imaging (EPI) scans, acquired during the aforementioned tasks and resting state. The data includes several self-report measures related to perseverative thinking, emotion regulation, and imaginative processes, along with a behavioral measure of rapid visual information processing. Technical validation of the data confirms that the tasks deactivate and activate the DMN as expected. Group level analysis of the neurofeedback data indicates that the participants are able to modulate their DMN with considerable inter-subject variability. Preliminary analysis of behavioral responses and specifically self-reported sleep indicate that as many as 73 participants may need to be excluded from an analysis depending on the hypothesis being tested. The present data are linked to the enhanced Nathan Kline Institute, Rockland Sample and builds on the comprehensive neuroimaging and deep phenotyping available therein. As limited information is presently available about individual differences in the capacity to directly modulate the default mode network, these data provide a unique opportunity to examine DMN modulation ability in relation to numerous phenotypic characteristics.

Background visual motion affects responses of an insect motion-sensitive neuron to objects deviating from a collision course

Stimulus complexity affects the response of looming sensitive neurons in a variety of animal taxa. The Lobula Giant Movement Detector/Descending Contralateral Movement Detector (LGMD/DCMD) pathway is well-characterized in the locust visual system. It responds to simple objects approaching on a direct collision course (i.e., looming) as well as complex motion defined by changes in stimulus velocity, trajectory, and transitions, all of which are affected by the presence or absence of background visual motion. In this study, we focused on DCMD responses to objects transitioning away from a collision course, which emulates a successful locust avoidance behavior. We presented each of 20 locusts with a sequence of complex three-dimensional visual stimuli in simple, scattered, and progressive flow field backgrounds while simultaneously recording DCMD activity extracellularly. DCMD responses to looming stimuli were generally characteristic irrespective of stimulus background. However, changing background complexity affected, peak firing rates, peak time, and caused changes in peak rise and fall phases. The DCMD response to complex object motion also varied with the azimuthal approach angle and the dynamics of object edge expansion. These data fit with an existing correlational model that relates expansion properties to firing rate modulation during trajectory changes.