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Inhibition of return (IOR) refers to the slower response to a target appearing at a previously attended location in a cue–target paradigm. It has been greatly explored in the visual or auditory modality. This study investigates differences between the IOR of audiovisual targets and the IOR of visual targets under conditions of modality-specific selective attention (Experiment 1) and divided-modalities attention (Experiment 2). We employed an exogenous spatial cueing paradigm and manipulated the modalities of targets, including visual, auditory, or audiovisual modalities. The participants were asked to detect targets in visual modality or both visual and auditory modalities, which were presented on the same (cued) or opposite (uncued) side as the preceding visual peripheral cues. In Experiment 1, we found the comparable IOR with visual and audiovisual targets when participants were asked to selectively focus on visual modality. In Experiment 2, however, there was a smaller magnitude of IOR with audiovisual targets as compared with visual targets when paying attention to both visual and auditory modalities. We also observed a reduced multisensory response enhancement effect and race model inequality violation at cued locations relative to uncued locations. These results provide the first evidence of the IOR with audiovisual targets. Furthermore, IOR with audiovisual targets decreases when paying attention to both modalities. The interaction between exogenous spatial attention and audiovisual integration is discussed.

Early detection of Alzheimer's disease (AD) is critical due to its rising prevalence. AI-aided AD diagnosis has grown for decades. Most of these systems use deep learning using CNN. However, a few concerns must be addressed to identify AD: a. there is a lack of attention paid to spatial features; b. there is a lack of scale-invariant feature modelling; and c. the convolutional spatial attention block (C-SAB) mechanism is available in the literature, but it exploits limited feature sets from its input features to obtain a spatial attention map, which needs to be enhanced. The suggested model addresses these issues in two ways: through a backbone of multilayers of depth-separable CNN. Firstly, we propose an improved spatial convolution attention block (I-SAB) to generate an enhanced spatial attention map for the multilayer features of the backbone. The I-SAB, a modified version of the C-SAB, generates a spatial attention map by combining multiple cues from input feature maps. Such a map is forwarded to a multilayer of depth-separable CNN for further feature extraction and employs a skip connection to produce an enhanced spatial attention map. Second, we combine multilayer spatial attention features to make scale-invariant spatial attention features that can fix scale issues in MRI images. We demonstrate extensive experimentation and ablation studies using two open-source datasets, OASIS and AD-Dataset. The recommended model outperforms existing best practices with 99.75% and 96.20% accuracy on OASIS and AD-Dataset. This paper also performed a domain adaptation test on the OASIS dataset, which obtained 83.25% accuracy.

Intrinsic plasticity of neurons, such as spontaneous threshold lowering (STL) to modulate neuronal excitability, is key to spatial attention of biological neural systems. In‐memory computing with emerging memristors is expected to solve the memory bottleneck of the von Neumann architecture commonly used in conventional digital computers and is deemed a promising solution to this bioinspired computing paradigm. Nonetheless, conventional memristors are incapable of implementing the STL plasticity of neurons due to their first‐order dynamics. Here, a second‐order memristor is experimentally demonstrated using yttria‐stabilized zirconia with Ag doping (YSZ:Ag) that exhibits STL functionality. The physical origin of the second‐order dynamics, i.e., the size evolution of Ag nanoclusters, is uncovered through transmission electron microscopy (TEM), which is leveraged to model the STL neuron. STL‐based spatial attention in a spiking convolutional neural network (SCNN) is demonstrated, improving the accuracy of a multiobject detection task from 70% (20%) to 90% (80%) for the object within (outside) the area receiving attention. This second‐order memristor with intrinsic STL dynamics paves the way for future machine intelligence, enabling high‐efficiency, compact footprint, and hardware‐encoded plasticity. Spontaneous threshold lowering (STL) originates from the intrinsic neuronal plasticity observed in biological neurons, which plays an important role in a number of learning protocols like spatial attention. Here for the first time artificial STL neurons using second‐order yttria‐stabilized zirconia with Ag doping (YSZ:Ag) memristors at a small hardware overhead are realized, which mimic neural intrinsic plasticity and boost the performance of spiking neural networks.

Research has shown improved reading following visual magnocellular training in individuals with dyslexia. Many studies have demonstrated how the magnocellular pathway controls visual spatial attention. Therefore, we have investigated the relationship between magnocellular pathway and visual spatial attention deficits in dyslexia in order to better understand how magnocellular-based interventions may help children to learn to read. Magnocellular function, visual spatial attention, and reading abilities of thirty elementary school students with dyslexia, aged between 8 and 10, were measured. The experimental group received magnocellular-based visual motion training for 12 sessions, while the control group received neutral sessions. All tests were repeated at the end of the training and after 1 month. The magnocellular functioning, visual spatial attention, and reading abilities of the experimental group improved significantly compared to the controls. Additionally, improvement in reaction time of invalid conditions predicted improvements in saccadic eye movements. We conclude that visual magnocellular training improved saccadic eye movement control, visual spatial orientation, and reading ability.

Visual-spatial selective attention enhances the processing of task-relevant visual events while suppressing the processing of irrelevant ones. In this study, we employed a frequency-tagging paradigm to investigate how sustained visual-spatial attention modulates the first harmonic and second harmonic steady-state visual evoked potentials (SSVEPs). Unlike previous studies, that investigated stimulation durations of 10 s or less, we tested a 30-s period. SSVEPs were elicited by simultaneously presenting to the right and left visual hemifields two pattern reversal checkerboard stimuli modulating at 7.14 Hz and 11.11 Hz. Participants were cued to selectively attend to one visual hemifield while ignoring the other. Behavioral results indicated that participants selectively attended to the cued visual hemifield. When participants attended to the visual stimuli, there were larger second harmonic SSVEPs but no attentional modulation of first harmonics. The results are consistent with the proposal that neural populations underlying first, and second harmonics have distinct functional roles, i.e., first harmonics’ mechanisms preserve stimulus properties and are resistant to attentional gain, whereas second harmonics mediate attentional modulation. This interpretation is supported by a gain control theory of selective attention.

The present study investigated the associations of visual-spatial attention with word reading fluency and spelling in 92 third grade Hong Kong Chinese children. Word reading fluency was measured with a timed reading task whereas spelling was measured with a dictation task. Results showed that visual-spatial attention was a unique predictor of speeded reading accuracy (i.e., the total number of words read correctly divided by the total number of words read in a timed reading task) but not reading speed (i.e., the number of words read correctly in the same task) after controlling for age, non-verbal intelligence, morphological awareness, phonological awareness, orthographic knowledge, and rapid automatized naming. Visual-spatial attention also explained unique variance in word spelling measured with a dictation task after the same control variables. The findings of the present study suggest that visual-spatial attention is important for literacy development in Chinese children.

Diabetic Retinopathy is one of the prominent reasons for permanent blindness in working age, long term diabetic patients. With the prevalence in raise of diabetics, majority of the people are endangered to permanent vision loss. The advancements in medical imaging techniques enabled the research community to focus on developing automated and computerized systems for diagnosing retinopathy in early stages. But, it is a very complex challenge due to the presence of high intra-class variations and imbalanced data distribution for higher grades of severity. In recent years, various deep learning based models have been designed for automating the process of retinopathy severity classification. In this research work, we present a fascinating deep learning model with multiple attention stages called Hinge Attention Network (HA-Net). Proposed model consists of a pre-trained VGG16 base to extract initial spatial representation from retinal scan images, spatial attention autoencoder to learn lesion specific latent representations in spatial dimensions and a channel attention based hinge neural network to grab category based discriminative features in channel dimension and classify the severity grade of retinopathy. In addition to spatial and channel attention mechanism, we use Convolutional LSTM layer to prioritize highly important spatial maps before passing to hinge neural network. All these components of HA-Net, enabled it to make generalised and accurate predictions on unseen data. The effectiveness and acceptability of proposed model is proved by validating it using two benchmark datasets, Kaggle APTOS 2019 and ISBI IDRiD. Extensive experimental studies on these datasets reveal that, proposed HA-Net outstrip several existing models by achieving an accuracy of 85.54% on Kaggle APTOS, and an accuracy of 66.41% on IDRiD datasets.

When two tasks, Task 1 and Task 2, are conducted in close temporal proximity and a separate speeded response is required for each target (T1 and T2), T2 report performance decreases as a function of its temporal proximity to T1. This so-called psychological refractory period (PRP) effect on T2 processing is largely assumed to reflect interference from T1 response selection on T2 response selection. However, interference on early perceptual processing of T2 has been observed in a modified paradigm, which required changes in visual-spatial attention, sensory modality, task modality, and response modality across targets. The goal of the present study was to investigate the possibility of early perceptual interference by systematically and iteratively removing each of these possible non perceptual confounds, in a series of four experiments. To assess T2 visual memory consolidation success, T2 was presented for a varying duration and immediately masked. T2 report accuracy, which was taken as a measure of perceptual—encoding or consolidation—success, decreased across all experimental control conditions as T1–T2 onset proximity increased. We argue that our results, in light of previous studies, show that central processing of a first target, responsible for the classical PRP effect, also interferes with early perceptual processing of a second target. We end with a discussion of broader implications for psychological refractory period and attentional blink effects.

The present study aimed to investigate the effect of adolescents’ perceived negative evaluation of parenting on their visuo-spatial attention and mental rotation abilities. The useful field of view (UFOV) and mental rotation tasks were used to measure visuo-spatial attention and mental rotation abilities among adolescents. The experimental groups were divided into the negatively evaluating group (MAge = 18.44, SD = 0.87, 20.7% girls) and positively evaluating group (MAge = 18.40, SD = 0.81, 23.3% girls) based on their scores on the self-perceived parenting attitude scales. The UFOV task showed lesser accuracy of the negatively evaluating group when compared to the positively evaluating one in target perception presented in 20° visual angle, indicating a deteriorated visuo-spatial attention ability in the negatively evaluating group. In the mental rotation task, the negatively evaluating group exhibited a small trade-off effect between response times and rotation angles, which implied an impatient strategy was employed to perform the task, whereas such a trade-off was not observed in the positively evaluating group. Thus, both experimental groups differed in terms of their visual attention and mental spatial abilities. This study suggests that the reduced visuo-spatial attention and mental rotation abilities may act as precursors for serious psychological symptoms caused by the negative self-evaluation of their parents’ parenting attitudes.

A method for the conversion of SAR (Synthetic Aperture Radar) images to optical images can be useful for disaster area detection for the following two reasons: (1) it is easier to detect disaster areas with optical images rather than with SAR images; (2) disasters may occur at night and in rainy and cloudy conditions (SAR images can be acquired in daytime and nighttime as well as all weather conditions). Therefore, it becomes easier to detect disaster areas with optical images converted from SAR images. Using GANs (Generative Adversarial Networks), it is possible to convert SAR images to optical images. In particular, pix2pix and pix2pixHD are used for this purpose. The author proposed spatial resolution-maintained pix2pixHD previously. In this paper, a new method of modifying pix2pixHD with a spatial attention mechanism and an edge enhancement mechanism with a Canny filter in the loss function is proposed, and the proposed method is compared to the pix2pixHD with a spatial attention mechanism and pix2pixHD as well as pix2pix. All of these four methods are compared in terms of the spatial resolution (frequency components) of converted optical images. By experiment, the superiority of the modified pix2pixHD with spatial attention and edge enhancement mechanisms is confirmed for disaster area detection (landslide area detection).