Attention modulates early visual processing: An association between subjective contrast perception and early C1 ERP component

The question of whether spatial attention can modulate initial afferent activity in area V1, as measured by the earliest visual event-related potential (ERP) component "C1", is still the subject of debate. Because attention always enhances behavioral performance, previous research has focused on finding evidence of attention-related enhancements in visual neural responses. However, recent psychophysical studies revealed a complex picture of attention's influence on visual perception: attention amplifies the perceived contrast of low-contrast stimuli while dampening the perceived contrast of high-contrast stimuli. This evidence suggests that attention may not invariably augment visual neural responses but could instead exert inhibitory effects under certain circumstances. Whether this bi-directional modulation of attention also manifests in C1 and whether the modulation of C1 underpins the attentional influence on contrast perception remain unknown. To address these questions, we conducted two experiments (N = 67 in total) by employing a combination of behavioral and ERP methodologies. Our results did not unveil a uniform attentional enhancement or attenuation effect of C1 across all subjects. However, an intriguing correlation between the attentional effects of C1 and contrast appearance for high-contrast stimuli did emerge, revealing an association between attentional modulation of C1 and the attentional modulation of contrast appearance. This finding offers new insights into the relationship between attention, perceptual experience, and early visual neural processing, suggesting that the attentional effect on subjective visual perception could be mediated by the attentional modulation of the earliest visual cortical response.

Children with dyslexia show no deficit in exogenous spatial attention but show differences in visual encoding

In the search for mechanisms that contribute to dyslexia, the term "attention" has been invoked to explain performance in a variety of tasks, creating confusion since all tasks do, indeed, demand "attention." Many studies lack an experimental manipulation of attention that would be necessary to determine its influence on task performance. Nonetheless, an emerging view is that children with dyslexia have an impairment in the exogenous (automatic/reflexive) orienting of spatial attention. Here we investigated the link between exogenous attention and reading ability by presenting exogenous spatial cues in the multi-letter processing task-a task relevant for reading. The task was gamified and administered online to a large sample of children (N = 187) between 6 and 17 years. Children with dyslexia performed worse overall at rapidly recognizing and reporting strings of letters. However, we found no evidence for a difference in the utilization of exogenous spatial cues, resolving two decades of ambiguity in the field. Previous studies that claimed otherwise may have failed to distinguish attention effects from overall task performance or found spurious group differences in small samples. RESEARCH HIGHLIGHTS: We manipulated exogenous visual spatial attention using pre-cues in a task that is relevant for reading and we see robust task effects of exogenous attention. We found no evidence for a deficit in utilizing exogenous spatial pre-cues in children with dyslexia. However, children with dyslexia showed reduced recognition ability for all letter positions. Children with dyslexia were just as likely to make letter transposition errors as typical readers.

Dynamic alpha power modulations and slow negative potentials track natural shifts of spatio-temporal attention

Alpha power modulations and slow negative potentials have previously been associated with anticipatory processes in spatial and temporal top-down attention. In typical experimental designs, however, neural responses triggered by transient stimulus onsets can interfere with attention-driven activity patterns and our interpretation of such. Here, we investigated these signatures of spatio-temporal attention in a dynamic paradigm free from potentially confounding stimulus-driven activity using electroencephalography. Participants attended the cued side of a bilateral stimulus rotation and mentally counted how often one of two remembered sample orientations (i.e., the target) was displayed while ignoring the uncued side and non-target orientation. Afterwards, participants performed a delayed match-to-sample task, in which they indicated if the orientation of a probe stimulus matched the corresponding sample orientation (previously target or non-target). We observed dynamic alpha power reductions and slow negative waves around task-relevant points in space and time (i.e., onset of the target orientation in the cued hemifield) over posterior electrodes contralateral to the locus of attention. In contrast to static alpha power lateralization, these dynamic signatures correlated with subsequent memory performance (primarily detriments for matching probes of the non-target orientation), suggesting a preferential allocation of attention to task-relevant locations and time points at the expense of reduced resources and impaired performance for information outside the current focus of attention. Our findings suggest that humans can naturally and dynamically focus their attention at relevant points in space and time and that such spatio-temporal attention shifts can be reflected by dynamic alpha power modulations and slow negative potentials.

Reduced Visuospatial Attention in Personal Space is Not Limited to the Affected Limb in Complex Regional Pain Syndrome

Purpose

Alterations in spatial attention have been reported in people with chronic pain and may be relevant to understanding its cortical mechanisms and developing novel treatments. There is conflicting evidence as to whether people with Complex Regional Pain Syndrome (CRPS) have reduced visuospatial attention to their affected limb and/or its surrounding space, with some evidence that these deficits may be greater in personal (bodily) space. We aimed to test the competing hypotheses of whether the visuospatial attentional bias is specific to the personal space of the affected limb or generalizes to the personal space of other parts of the affected side of the body.

Patients and Methods

Using visual Temporal Order Judgement tasks, we measured spatial attention in the personal space of the hands and feet of patients with upper (n=14) or lower (n=14) limb CRPS and pain-free controls (n=17). Participants judged the order of two light flashes presented at different temporal offsets on each of their hands or feet. Slower processing of the flash on one side relative to the other reflects reduced attention to that side of space.

Results

Controls prioritized stimuli on the non-dominant (left) relative to dominant side, consistent with the well-documented normal leftward bias of attention (ie "pseudoneglect"). Regardless of the location (upper or lower limb) of the pain or visual stimuli, people with CRPS showed no such asymmetry, representing reduced attention to the affected side (compared to the greater attention of controls to their non-dominant side). More severe CRPS symptoms were associated with a greater tendency to deprioritize stimuli on the affected side.

Conclusion

Our findings suggest that relative visuospatial bias in CRPS is generalized to the personal space of the affected side of the body, rather than being specific to the personal space of the CRPS-affected limb.

An attentional approach to geometrical illusions

It is known for a long time that some drawings composed of points, lines, and areas are systematically misperceived. The origin of these geometrical illusions is still unknown. Here we outline how a recent progress in attentional research contributes to a better understanding of such perceptual distortions. The basic idea behind this approach is that crucial elements of a drawing are differently attended. These changes in the allocation of spatial attention go along with systematic changes in low-level spatial coding. As a result, changes in the perception of spatial extent, angles, positions, and shapes can arise. How this approach can be applied to individual illusions is discussed.

Classification Algorithm for fNIRS-based Brain Signals Using Convolutional Neural Network with Spatiotemporal Feature Extraction Mechanism

Brain Computer Interface (BCI) is a highly promising human-computer interaction method that can utilize brain signals to control external devices. BCI based on functional near-infrared spectroscopy (fNIRS) is considered a relatively new and promising paradigm. fNIRS is a technique of measuring functional changes in cerebral hemodynamics. It detects changes in the hemodynamic activity of the cerebral cortex by measuring oxyhemoglobin and deoxyhemoglobin (HbR) concentrations and inversely predicts the neural activity of the brain. At the present time, Deep learning (DL) methods have not been widely used in fNIRS decoding, and there are fewer studies considering both spatial and temporal dimensions for fNIRS classification. To solve these problems, we proposed an end-to-end hybrid neural network for feature extraction of fNIRS. The method utilizes a spatial-temporal convolutional layer for automatic extraction of temporally valid information and uses a spatial attention mechanism to extract spatially localized information. A temporal convolutional network (TCN) is used to further utilize the temporal information of fNIRS before the fully connected layer. We validated our approach on a publicly available dataset including 29 subjects, including left-hand and right-hand motor imagery (MI), mental arithmetic (MA), and a baseline task. The results show that the method has few training parameters and high accuracy, providing a meaningful reference for BCI development.

Celiac disease diagnosis from endoscopic images based on multi-scale adaptive hybrid architecture model

Objective. Celiac disease (CD) has emerged as a significant global public health concern, exhibiting an estimated worldwide prevalence of approximately 1%. However, existing research pertaining to domestic occurrences of CD is confined mainly to case reports and limited case analyses. Furthermore, there is a substantial population of undiagnosed patients in the Xinjiang region. This study endeavors to create a novel, high-performance, lightweight deep learning model utilizing endoscopic images from CD patients in Xinjiang as a dataset, with the intention of enhancing the accuracy of CD diagnosis.Approach. In this study, we propose a novel CNN-Transformer hybrid architecture for deep learning, tailored to the diagnosis of CD using endoscopic images. Within this architecture, a multi-scale spatial adaptive selective kernel convolution feature attention module demonstrates remarkable efficacy in diagnosing CD. Within this module, we dynamically capture salient features within the local channel feature map that correspond to distinct manifestations of endoscopic image lesions in the CD-affected areas such as the duodenal bulb, duodenal descending segment, and terminal ileum. This process serves to extract and fortify the spatial information specific to different lesions. This strategic approach facilitates not only the extraction of diverse lesion characteristics but also the attentive consideration of their spatial distribution. Additionally, we integrate the global representation of the feature map obtained from the Transformer with the locally extracted information via convolutional layers. This integration achieves a harmonious synergy that optimizes the diagnostic prowess of the model.Main results. Overall, the accuracy, specificity, F1-Score, and precision in the experimental results were 98.38%, 99.04%, 98.66% and 99.38%, respectively.Significance. This study introduces a deep learning network equipped with both global feature response and local feature extraction capabilities. This innovative architecture holds significant promise for the accurate diagnosis of CD by leveraging endoscopic images captured from diverse anatomical sites.

Spatial attention alters visual cortical representation during target anticipation

Attention enables us to efficiently and flexibly interact with the environment by prioritizing some image features, such as location or orientation, even before stimulus onset. We investigated how covert spatial attention affects responses in human visual cortex prior to target onset and how it affects behavioral performance after target onset, using a concurrent psychophysics-fMRI experiment. Performance improved at cued locations and worsened at uncued locations, relative to distributed attention. BOLD responses in cortical visual field maps changed in two ways: First, there was a stimulus-independent baseline shift, positive in map locations near the cued location and negative elsewhere. Second, population receptive field centers shifted toward the attended location. Both effects increased in higher visual areas. Together, the results show that spatial attention has large effects on visual cortex prior to target appearance, altering neural response properties across the entirety of multiple visual field maps.

Attentional bias towards happy faces in the dot-probe paradigm: it depends on which task is used

Two recent articles [Gronchi et al., 2018. Automatic and controlled attentional orienting in the elderly: A dual-process view of the positivity effect. Acta Psychologica, 185, 229-234; Wirth & Wentura, 2020. It occurs after all: Attentional bias towards happy faces in the dot-probe task. Attention, Perception, & Psychophysics, 82(5), 2463-2481] report attentional biases for happy facial expressions in the dot-probe paradigm, albeit in different directions. While Wirth and Wentura report a bias towards happy expressions, Gronchi et al. found a reversed effect. A striking difference between the studies was the task performed by the participants. While in Wirth and Wentura, participants performed a discrimination task, they performed a location task in Gronchi et al. In Experiment 1, we directly compared the two versions of the dot-probe paradigm. With the discrimination task, the bias towards happy faces was replicated. However, the location task yielded a null effect. In Experiment 2, we found a cueing effect with an abrupt onset cue in both tasks. However, for the location task a congruence-sequence effect (a typical characteristic of response-priming processes) occurred. This result suggests that in the location task, attentional processes are confounded with response-priming processes. We recommend to generally use discrimination tasks.

Eye movements reveal that young school children shift attention when solving additions and subtractions

Adults shift their attention to the right or to the left along a spatial continuum when solving additions and subtractions, respectively. Studies suggest that these shifts not only support the exact computation of the results but also anticipatively narrow down the range of plausible answers when processing the operands. However, little is known on when and how these attentional shifts arise in childhood during the acquisition of arithmetic. Here, an eye-tracker with high spatio-temporal resolution was used to measure spontaneous eye movements, used as a proxy for attentional shifts, while children of 2nd (8 y-o; N = 50) and 4th (10 y-o; N = 48) Grade solved simple additions (e.g., 4+3) and subtractions (e.g., 3-2). Gaze patterns revealed horizontal and vertical attentional shifts in both groups. Critically, horizontal eye movements were observed in 4th Graders as soon as the first operand and the operator were presented and thus before the beginning of the exact computation. In 2nd Graders, attentional shifts were only observed after the presentation of the second operand just before the response was made. This demonstrates that spatial attention is recruited when children solve arithmetic problems, even in the early stages of learning mathematics. The time course of these attentional shifts suggests that with practice in arithmetic children start to use spatial attention to anticipatively guide the search for the answer and facilitate the implementation of solving procedures. RESEARCH HIGHLIGHTS: Additions and subtractions are associated to right and left attentional shifts in adults, but it is unknown when these mechanisms arise in childhood. Children of 8-10 years old solved single-digit additions and subtractions while looking at a blank screen. Eye movements showed that children of 8 years old already show spatial biases possibly to represent the response when knowing both operands. Children of 10 years old shift attention before knowing the second operand to anticipatively guide the search for plausible answers.

Spatial attention and central crowding in primary open angle glaucoma

CLINICAL RELEVANCE

Measuring the impact of spatial attention on signal detection in damaged parts of the visual field can be a useful tool for eye care practitioners.

BACKGROUND

Studies on letter perception have shown that glaucoma exacerbates difficulties to detect a target within flankers (crowding) in parafoveal vision. A target can be missed because it is not seen or because attention was not focused at that location. This prospective study evaluates the contribution of spatial pre-cueing on target detection.

METHOD

Fifteen patients and 15 age-matched controls were presented with letters displayed for 200 ms. Participants were asked to identify the orientation of the target letter T in two conditions: an isolated letter (uncrowded condition) and a letter with two flankers (crowded condition). The spacing between target and flankers was manipulated. The stimuli were randomly displayed at the fovea and at the parafovea at 5° left or right of fixation. A spatial cue preceded the stimuli in 50% of the trials. When present, the cue always signalled the correct location of the target.

RESULTS

Pre-cueing the spatial location of the target significantly improved performance for both foveal and parafoveal presentations in patients but not in controls who were at ceiling level. Unlike controls, patients exhibited an effect of crowding at the fovea with a higher accuracy for the isolated target than for the target flanked by two letters with no spacing between the elements.

CONCLUSION

Higher susceptibility to central crowding supports data showing abnormal foveal vision in glaucoma. Exogenous orienting of attention facilitates perception in parts of the visual field with reduced sensitivity.

CESA-MCFormer: An Efficient Transformer Network for Hyperspectral Image Classification by Eliminating Redundant Information

Hyperspectral image (HSI) classification is a highly challenging task, particularly in fields like crop yield prediction and agricultural infrastructure detection. These applications often involve complex image types, such as soil, vegetation, water bodies, and urban structures, encompassing a variety of surface features. In HSI, the strong correlation between adjacent bands leads to redundancy in spectral information, while using image patches as the basic unit of classification causes redundancy in spatial information. To more effectively extract key information from this massive redundancy for classification, we innovatively proposed the CESA-MCFormer model, building upon the transformer architecture with the introduction of the Center Enhanced Spatial Attention (CESA) module and Morphological Convolution (MC). The CESA module combines hard coding and soft coding to provide the model with prior spatial information before the mixing of spatial features, introducing comprehensive spatial information. MC employs a series of learnable pooling operations, not only extracting key details in both spatial and spectral dimensions but also effectively merging this information. By integrating the CESA module and MC, the CESA-MCFormer model employs a "Selection-Extraction" feature processing strategy, enabling it to achieve precise classification with minimal samples, without relying on dimension reduction techniques such as PCA. To thoroughly evaluate our method, we conducted extensive experiments on the IP, UP, and Chikusei datasets, comparing our method with the latest advanced approaches. The experimental results demonstrate that the CESA-MCFormer achieved outstanding performance on all three test datasets, with Kappa coefficients of 96.38%, 98.24%, and 99.53%, respectively.

A Lightweight Image Super-Resolution Reconstruction Algorithm Based on the Residual Feature Distillation Mechanism

In recent years, the development of image super-resolution (SR) has explored the capabilities of convolutional neural networks (CNNs). The current research tends to use deeper CNNs to improve performance. However, blindly increasing the depth of the network does not effectively enhance its performance. Moreover, as the network depth increases, more issues arise during the training process, requiring additional training techniques. In this paper, we propose a lightweight image super-resolution reconstruction algorithm (SISR-RFDM) based on the residual feature distillation mechanism (RFDM). Building upon residual blocks, we introduce spatial attention (SA) modules to provide more informative cues for recovering high-frequency details such as image edges and textures. Additionally, the output of each residual block is utilized as hierarchical features for global feature fusion (GFF), enhancing inter-layer information flow and feature reuse. Finally, all these features are fed into the reconstruction module to restore high-quality images. Experimental results demonstrate that our proposed algorithm outperforms other comparative algorithms in terms of both subjective visual effects and objective evaluation quality. The peak signal-to-noise ratio (PSNR) is improved by 0.23 dB, and the structural similarity index (SSIM) reaches 0.9607.

Spatial attention modulates multisensory integration: The dissociation between exogenous and endogenous orienting

Previous studies have separately found that exogenous orienting decreases multisensory integration (MSI), while endogenous orienting enhances MSI. It is currently unclear, however, why the two orientations have opposite effects on MSI. In the current study, we investigated the interaction between spatial attention and MSI in two experiments based on the cue-target paradigm. Experiment 1 separated exogenous and endogenous orienting to investigate the effect of spatial attention on MSI by varying the predictability of the cue. Experiment 2 further explored the effect of endogenous orienting on MSI. We found that exogenous orienting induced by the directionality of the cue decreased MSI, while endogenous orienting induced by the predictability of the cue enhanced MSI. The role of spatial orienting need and spatial attention bias in the modulation of MSI by exogenous and endogenous orienting was discussed. The present study sheds new light on how spatial attention modulates MSI processes.

Distinct patterns of spatial attentional modulation of steady-state visual evoked magnetic fields (SSVEFs) in subdivisions of the human early visual cortex

In recent years, steady-state visual evoked potentials (SSVEPs) became an increasingly valuable tool to investigate neural dynamics of competitive attentional interactions and brain-computer interfaces. This is due to their good signal-to-noise ratio, allowing for single-trial analysis, and their ongoing oscillating nature that enables to analyze temporal dynamics of facilitation and suppression. Given the popularity of SSVEPs, it is surprising that only a few studies looked at the cortical sources of these responses. This is in particular the case when searching for studies that assessed the cortical sources of attentional SSVEP amplitude modulations. To address this issue, we used a typical spatial attention task and recorded neuromagnetic fields (MEG) while presenting frequency-tagged stimuli in the left and right visual fields, respectively. Importantly, we controlled for attentional deployment in a baseline period before the shifting cue. Subjects either attended to a central fixation cross or to two peripheral stimuli simultaneously. Results clearly showed that signal sources and attention effects were restricted to the early visual cortex: V1, V2, hMT+, precuneus, occipital-parietal, and inferior-temporal cortex. When subjects attended to central fixation first, shifting attention to one of the peripheral stimuli resulted in a significant activation increase for the to-be-attended stimulus with no activation decrease for the to-be-ignored stimulus in hMT+ and inferio-temporal cortex, but significant SSVEF decreases from V1 to occipito-parietal cortex. When attention was first deployed to both rings, shifting attention away from one ring basically resulted in a significant activation decrease in all areas for the then-to-be-ignored stimulus.

Representational structures as a unifying framework for attention

Our visual system consciously processes only a subset of the incoming information. Selective attention allows us to prioritize relevant inputs, and can be allocated to features, locations, and objects. Recent advances in feature-based attention suggest that several selection principles are shared across these domains and that many differences between the effects of attention on perceptual processing can be explained by differences in the underlying representational structures. Moving forward, it can thus be useful to assess how attention changes the structure of the representational spaces over which it operates, which include the spatial organization, feature maps, and object-based coding in visual cortex. This will ultimately add to our understanding of how attention changes the flow of visual information processing more broadly.

fNIRS Dataset During Complex Scene Analysis

When analyzing complex scenes, humans often focus their attention on an object at a particular spatial location. The ability to decode the attended spatial location would facilitate brain computer interfaces for complex scene analysis (CSA). Here, we investigated capability of functional near-infrared spectroscopy (fNIRS) to decode audio-visual spatial attention in the presence of competing stimuli from multiple locations. We targeted dorsal frontoparietal network including frontal eye field (FEF) and intra-parietal sulcus (IPS) as well as superior temporal gyrus/planum temporal (STG/PT). They all were shown in previous functional magnetic resonance imaging (fMRI) studies to be activated by auditory, visual, or audio-visual spatial tasks. To date, fNIRS has not been applied to decode auditory and visual-spatial attention during CSA, and thus, no such dataset exists yet. This report provides an open-access fNIRS dataset that can be used to develop, test, and compare machine learning algorithms for classifying attended locations based on the fNIRS signals on a single trial basis.

Efficient Human Violence Recognition for Surveillance in Real Time

Human violence recognition is an area of great interest in the scientific community due to its broad spectrum of applications, especially in video surveillance systems, because detecting violence in real time can prevent criminal acts and save lives. The majority of existing proposals and studies focus on result precision, neglecting efficiency and practical implementations. Thus, in this work, we propose a model that is effective and efficient in recognizing human violence in real time. The proposed model consists of three modules: the Spatial Motion Extractor (SME) module, which extracts regions of interest from a frame; the Short Temporal Extractor (STE) module, which extracts temporal characteristics of rapid movements; and the Global Temporal Extractor (GTE) module, which is responsible for identifying long-lasting temporal features and fine-tuning the model. The proposal was evaluated for its efficiency, effectiveness, and ability to operate in real time. The results obtained on the Hockey, Movies, and RWF-2000 datasets demonstrated that this approach is highly efficient compared to various alternatives. In addition, the VioPeru dataset was created, which contains violent and non-violent videos captured by real video surveillance cameras in Peru, to validate the real-time applicability of the model. When tested on this dataset, the effectiveness of our model was superior to the best existing models.

Pathway-selective optogenetics reveals the functional anatomy of top-down attentional modulation in the macaque visual cortex

Spatial attention represents a powerful top-down influence on sensory responses in primate visual cortical areas. The frontal eye field (FEF) has emerged as a key candidate area for the source of this modulation. However, it is unclear whether the FEF exerts its effects via its direct axonal projections to visual areas or indirectly through other brain areas and whether the FEF affects both the enhancement of attended and the suppression of unattended sensory responses. We used pathway-selective optogenetics in rhesus macaques performing a spatial attention task to inhibit the direct input from the FEF to area MT, an area along the dorsal visual pathway specialized for the processing of visual motion information. Our results show that the optogenetic inhibition of the FEF input specifically reduces attentional modulation in MT by about a third without affecting the neurons' sensory response component. We find that the direct FEF-to-MT pathway contributes to both the enhanced processing of target stimuli and the suppression of distractors. The FEF, thus, selectively modulates firing rates in visual area MT, and it does so via its direct axonal projections.

Alpha and SSVEP power outperform gamma power in capturing attentional modulation in human EEG

Attention typically reduces power in the alpha (8-12 Hz) band and increases power in gamma (>30 Hz) band in brain signals, as reported in macaque local field potential (LFP) and human electro/magneto-encephalogram (EEG/MEG) studies. In addition, EEG studies often use flickering stimuli that produce a specific measure called steady-state-visually-evoked-potential (SSVEP), whose power also increases with attention. However, effectiveness of these neural measures in capturing attentional modulation is unknown since stimuli and task paradigms vary widely across studies. In a recent macaque study, attentional modulation was more salient in the gamma band of the LFP, compared to alpha or SSVEP. To compare this with human EEG, we designed an orientation change detection task where we presented both static and counterphasing stimuli of matched difficulty levels to 26 subjects and compared attentional modulation of various measures under similar conditions. We report two main results. First, attentional modulation was comparable for SSVEP and alpha. Second, non-foveal stimuli produced weak gamma despite various stimulus optimizations and showed negligible attentional modulation although full-screen gratings showed robust gamma activity. Our results are useful for brain-machine-interfacing studies where suitable features are used for decoding attention, and also provide clues about spatial scales of neural mechanisms underlying attention.

Automatic Detection and Classification of Hypertensive Retinopathy with Improved Convolution Neural Network and Improved SVM

Hypertensive retinopathy (HR) results from the microvascular retinal changes triggered by hypertension, which is the most common leading cause of preventable blindness worldwide. Therefore, it is necessary to develop an automated system for HR detection and evaluation using retinal images. We aimed to propose an automated approach to identify and categorize the various degrees of HR severity. A new network called the spatial convolution module (SCM) combines cross-channel and spatial information, and the convolution operations extract helpful features. The present model is evaluated using publicly accessible datasets ODIR, INSPIREVR, and VICAVR. We applied the augmentation to artificially increase the dataset of 1200 fundus images. The different HR severity levels of normal, mild, moderate, severe, and malignant are finally classified with the reduced time when compared to the existing models because in the proposed model, convolutional layers run only once on the input fundus images, which leads to a speedup and reduces the processing time in detecting the abnormalities in the vascular structure. According to the findings, the improved SVM had the highest detection and classification accuracy rate in the vessel classification with an accuracy of 98.99% and completed the task in 160.4 s. The ten-fold classification achieved the highest accuracy of 98.99%, i.e., 0.27 higher than the five-fold classification accuracy and the improved KNN classifier achieved an accuracy of 98.72%. When computation efficiency is a priority, the proposed model's ability to quickly recognize different HR severity levels is significant.

Integrating Simultaneous Motor Imagery and Spatial Attention for EEG-BCI Control

OBJECTIVE

EEG-based brain-computer interfaces (BCI) are non-invasive approaches for replacing or restoring motor functions in impaired patients, and direct brain-to-device communication in the general population. Motor imagery (MI) is one of the most used BCI paradigms, but its performance varies across individuals and certain users require substantial training to develop control. In this study, we propose to integrate a MI paradigm simultaneously with a recently proposed Overt Spatial Attention (OSA) paradigm, to accomplish BCI control.

METHODS

We evaluated a cohort of 25 human subjects' ability to control a virtual cursor in one- and two-dimensions over 5 BCI sessions. The subjects used 5 different BCI paradigms: MI alone, OSA alone, MI, and OSA simultaneously towards the same target (MI+OSA), and MI for one axis while OSA controls the other (MI/OSA and OSA/MI).

RESULTS

Our results show that MI+OSA reached the highest average online performance in 2D tasks at 49% Percent Valid Correct (PVC), and statistically outperforms both MI alone (42%) and OSA alone (45%). MI+OSA had a similar performance to each subject's best individual method between MI alone and OSA alone (50%) and 9 subjects reached their highest average BCI performance using MI+OSA.

CONCLUSION

Integrating MI and OSA leads to improved performance over both individual methods at the group level and is the best BCI paradigm option for some subjects.

SIGNIFICANCE

This work proposes a new BCI control paradigm that integrates two existing paradigms and demonstrates its value by showing that it can improve users' BCI performance.

Spatial Attention in Visual Working Memory Strengthens Feature-Location Binding

There is a debate about whether working memory (WM) representations are individual features or bound objects. While spatial attention is reported to play a significant role in feature binding, little is known about the role of spatial attention in WM. To address this gap, the current study required participants to maintain multiple items in their WM and employed a memory-driven attention capture paradigm. Spatial attention in WM was manipulated by presenting an exogenous cue at one of the locations that memory items had occupied. The effects of spatial attention on attention guidance in visual search (Experiment 1) and memory performance (Experiments 1 and 2) were explored. The results show that WM-driven attention guidance did not vary based on whether the search features came from the same object in WM; instead, it depended on the number of features, regardless of their source object. In memory tasks, the cued object outperformed the uncued object. Specifically, the test item was better rejected when the features were mis-bound in the cued location than in the uncued location. These findings suggest that memory-driven attention guidance is feature-based, and spatial attention in WM helps bind features into object structures based on location.

Beta oscillations in vision: a (preconscious) neural mechanism for the dorsal visual stream?

Neural oscillations in alpha (8-12 Hz) and beta (13-30 Hz) frequency bands are thought to reflect feedback/reentrant loops and large-scale cortical interactions. In the last decades a main effort has been made in linking perception with alpha-band oscillations, with converging evidence showing that alpha oscillations have a key role in the temporal and featural binding of visual input, configuring the alpha rhythm a key determinant of conscious visual experience. Less attention has been historically dedicated to link beta oscillations and visual processing. Nonetheless, increasing studies report that task conditions that require to segregate/integrate stimuli in space, to disentangle local/global shapes, to spatially reorganize visual inputs, and to achieve motion perception or form-motion integration, rely on the activity of beta oscillations, with a main hub in parietal areas. In the present review, we summarize the evidence linking oscillations within the beta band and visual perception. We propose that beta oscillations represent a neural code that supports the functionality of the magnocellular-dorsal (M-D) visual pathway, serving as a fast primary neural code to exert top-down influences on the slower parvocellular-ventral visual pathway activity. Such M-D-related beta activity is proposed to act mainly pre-consciously, providing the spatial coordinates of vision and guiding the conscious extraction of objects identity that are achieved with slower alpha rhythms in ventral areas. Finally, within this new theoretical framework, we discuss the potential role of M-D-related beta oscillations in visuo-spatial attention, oculo-motor behavior and reading (dis)abilities.

Perifoveal and peripheral attentional modulation on order perception

The present study demonstrates that spatial attention modulates temporal order perception differently in the perifoveal and peripheral regions, with a more pronounced effect in the left peripheral visual field, suggesting a dissociation in attentional systems for event timing at the sub-second level.

Catecholaminergic neuromodulation and selective attention jointly shape perceptual decision-making

Perceptual decisions about sensory input are influenced by fluctuations in ongoing neural activity, most prominently driven by attention and neuromodulator systems. It is currently unknown if neuromodulator activity and attention differentially modulate perceptual decision-making and/or whether neuromodulatory systems in fact control attentional processes. To investigate the effects of two distinct neuromodulatory systems and spatial attention on perceptual decisions, we pharmacologically elevated cholinergic (through donepezil) and catecholaminergic (through atomoxetine) levels in humans performing a visuo-spatial attention task, while we measured electroencephalography (EEG). Both attention and catecholaminergic enhancement improved decision-making at the behavioral and algorithmic level, as reflected in increased perceptual sensitivity and the modulation of the drift rate parameter derived from drift diffusion modeling. Univariate analyses of EEG data time-locked to the attentional cue, the target stimulus, and the motor response further revealed that attention and catecholaminergic enhancement both modulated pre-stimulus cortical excitability, cue- and stimulus-evoked sensory activity, as well as parietal evidence accumulation signals. Interestingly, we observed both similar, unique, and interactive effects of attention and catecholaminergic neuromodulation on these behavioral, algorithmic, and neural markers of the decision-making process. Thereby, this study reveals an intricate relationship between attentional and catecholaminergic systems and advances our understanding about how these systems jointly shape various stages of perceptual decision-making.

Periodic attention deficits after frontoparietal lesions provide causal evidence for rhythmic attentional sampling

Contemporary models conceptualize spatial attention as a blinking spotlight that sequentially samples visual space. Hence, behavior fluctuates over time, even in states of presumed "sustained" attention. Recent evidence has suggested that rhythmic neural activity in the frontoparietal network constitutes the functional basis of rhythmic attentional sampling. However, causal evidence to support this notion remains absent. Using a lateralized spatial attention task, we addressed this issue in patients with focal lesions in the frontoparietal attention network. Our results revealed that frontoparietal lesions introduce periodic attention deficits, i.e., temporally specific behavioral deficits that are aligned with the underlying neural oscillations. Attention-guided perceptual sensitivity was on par with that of healthy controls during optimal phases but was attenuated during the less excitable sub-cycles. Theta-dependent sampling (3-8 Hz) was causally dependent on the prefrontal cortex, while high-alpha/low-beta sampling (8-14 Hz) emerged from parietal areas. Collectively, our findings reveal that lesion-induced high-amplitude, low-frequency brain activity is not epiphenomenal but has immediate behavioral consequences. More generally, these results provide causal evidence for the hypothesis that the functional architecture of attention is inherently rhythmic.

No conclusive evidence for number-induced attentional shifts in a temporal order judgement task

The Spatial Numerical Association of Response Codes (SNARC) effect refers to the observation that relatively small (e.g., 1) and large numbers (e.g., 9) elicit faster left- and right-sided manual responses, respectively. In a variation known as the attentional SNARC effect, merely looking at numbers caused a left- or right-ward shift in covert spatial attention, depending on the number's magnitude. In our study, we probed the notion that numbers induce shifts of spatial attention in accordance with their position on a mental number line (MNL). Critically, we removed any putative spatial response code that may contaminate the responses. We used a square and a tilted square as targets, thereby situating the decisive response dimension in the ventral, non-spatial processing stream. In two experiments where numbers were used as non-informative cues preceding a temporal order judgement (TOJ) task, we did not observe a deflection of the locus of spatial attention as a function of the numerical magnitude of the cue. In a third experiment, finding a significant modulation of TOJ performance as a function of the pointing direction of arrow cues allowed us to rule out the possibility that the absence of any significant modulation in Experiments 1 and 2 was due to a lack of sensitivity of our task set-up. We conclude from the current findings that the spatial codes that the perception and naming of numbers potentially elicit are not in and by themselves sufficient to elicit deflections of spatial attention.

Rhythmic attentional sampling in autism

Individuals diagnosed with autism often display alterations in visual spatial attention toward visual stimuli, but the underlying cause of these differences remains unclear. Recent evidence has demonstrated that covert spatial attention, rather than remaining constant at a cued location, samples stimuli rhythmically at a frequency of 4-8 Hz (theta). Here we tested whether rhythmic sampling of attention is altered in autism. Participants were asked to monitor three locations to detect a brief target presented 300-1200 ms after a spatial cue. Visual attention was oriented to the cue and modified visual processing at the cued location, consistent with previous studies. We measured detection performance at different cue-target intervals when the target occurred at the cued location. Significant oscillations in detection performance were identified using both a traditional time-shuffled approach and a new autoregressive surrogate method developed by Brookshire in 2022. We found that attention enhances behavioral performance rhythmically at the same frequency in both autism and control group at the cued location. However, rhythmic temporal structure was not observed in a subgroup of autistic individuals with co-occurring attention-deficit/hyperactivity disorder (ADHD). Our results imply that intrinsic brain rhythms which organize neural activity into alternating attentional states is functional in autistic individuals, but may be altered in autistic participants who have a concurrent ADHD diagnosis.

Attention-Aware Patch-Based CNN for Blind 360-Degree Image Quality Assessment

An attention-aware patch-based deep-learning model for a blind 360-degree image quality assessment (360-IQA) is introduced in this paper. It employs spatial attention mechanisms to focus on spatially significant features, in addition to short skip connections to align them. A long skip connection is adopted to allow features from the earliest layers to be used at the final level. Patches are properly sampled on the sphere to correspond to the viewports displayed to the user using head-mounted displays. The sampling incorporates the relevance of patches by considering (i) the exploration behavior and (ii) a latitude-based selection. An adaptive strategy is applied to improve the pooling of local patch qualities to global image quality. This includes an outlier score rejection step relying on the standard deviation of the obtained scores to consider the agreement, as well as a saliency to weigh them based on their visual significance. Experiments on available 360-IQA databases show that our model outperforms the state of the art in terms of accuracy and generalization ability. This is valid for general deep-learning-based models, multichannel models, and natural scene statistic-based models. Furthermore, when compared to multichannel models, the computational complexity is significantly reduced. Finally, an extensive ablation study gives insights into the efficacy of each component of the proposed model.

Modeling the effects of transcranial magnetic stimulation on spatial attention

Objectives. Transcranial magnetic stimulation (TMS) has been widely used to modulate brain activity in healthy and diseased brains, but the underlying mechanisms are not fully understood. Previous research leveraged biophysical modeling of the induced electric field (E-field) to map causal structure-function relationships in the primary motor cortex. This study aims at transferring this localization approach to spatial attention, which helps to understand the TMS effects on cognitive functions, and may ultimately optimize stimulation schemes.Approach. Thirty right-handed healthy participants underwent a functional magnetic imaging (fMRI) experiment, and seventeen of them participated in a TMS experiment. The individual fMRI activation peak within the right inferior parietal lobule (rIPL) during a Posner-like attention task defined the center target for TMS. Thereafter, participants underwent 500 Posner task trials. During each trial, a 5-pulse burst of 10 Hz repetitive TMS (rTMS) was given over the rIPL to modulate attentional processing. The TMS-induced E-fields for every cortical target were correlated with the behavioral modulation to identify relevant cortical regions for attentional orientation and reorientation.Main results. We did not observe a robust correlation between E-field strength and behavioral outcomes, highlighting the challenges of transferring the localization method to cognitive functions with high neural response variability and complex network interactions. Nevertheless, TMS selectively inhibited attentional reorienting in five out of seventeen subjects, resulting in task-specific behavioral impairments. The BOLD-measured neuronal activity and TMS-evoked neuronal effects showed different patterns, which emphasizes the principal distinction between the neural activity being correlated with (or maybe even caused by) particular paradigms, and the activity of neural populations exerting a causal influence on the behavioral outcome.Significance. This study is the first to explore the mechanisms of TMS-induced attentional modulation through electrical field modeling. Our findings highlight the complexity of cognitive functions and provide a basis for optimizing attentional stimulation protocols.

The effects of visual distractors on serial dependence

Attractive serial dependence occurs when perceptual decisions are attracted toward previous stimuli. This effect is mediated by spatial attention and is most likely to occur when similar stimuli are attended at nearby locations. Attention, however, also involves the suppression of distracting information and of spatial locations where distracting stimuli have frequently appeared. Although distractors form an integral part of our visual experience, how they affect the processing of subsequent stimuli is unknown. Here, in two experiments, we tested serial dependence from distractor stimuli during an orientation adjustment task. We interleaved adjustment trials with a discrimination task requiring observers to ignore a peripheral distractor randomly appearing on half of the trials. Distractors were either similar to the adjustment probe (Experiment 1) or differed in spatial frequency and contrast (Experiment 2) and were shown at predictable or random locations in separate blocks. The results showed that the distractor caused considerable attentional capture in the discrimination task, with observers likely using proactive strategies to anticipate distractors at predictable locations. However, there was no evidence that the distractors affected the perceptual stream leading to positive serial dependence. Instead, they left a weak repulsive trace in Experiment 1 and more generally interfered with the effect of the previous adjustment probe in the serial dependence task. We suggest that this repulsive bias may reflect the operation of mechanisms involved in attentional suppression.

Involuntary shifts of spatial attention contribute to distraction-Evidence from oscillatory alpha power and reaction time data

Imagine you are focusing on the traffic on a busy street to ride your bike safely when suddenly you hear the siren of an ambulance. This unexpected sound involuntarily captures your attention and interferes with ongoing performance. We tested whether this type of distraction involves a spatial shift of attention. We measured behavioral data and magnetoencephalographic alpha power during a cross-modal paradigm that combined an exogenous cueing task and a distraction task. In each trial, a task-irrelevant sound preceded a visual target (left or right). The sound was usually the same animal sound (i.e., standard sound). Rarely, it was replaced by an unexpected environmental sound (i.e., deviant sound). Fifty percent of the deviants occurred on the same side as the target, and 50% occurred on the opposite side. Participants responded to the location of the target. As expected, responses were slower to targets that followed a deviant compared to a standard. Crucially, this distraction effect was mitigated by the spatial relationship between the targets and the deviants: responses were faster when targets followed deviants on the same versus different side, indexing a spatial shift of attention. This was further corroborated by a posterior alpha power modulation that was higher in the hemisphere ipsilateral (vs. contralateral) to the location of the attention-capturing deviant. We suggest that this alpha power lateralization reflects a spatial attention bias. Overall, our data support the contention that spatial shifts of attention contribute to deviant distraction.

Visual attention to features and space in mice using reverse correlation

Visual attention allows the brain to evoke behaviors based on the most important visual features. Mouse models offer immense potential to gain a circuit-level understanding of this phenomenon, yet how mice distribute attention across features and locations is not well understood. Here, we describe a new approach to address this limitation by training mice to detect weak vertical bars in a background of dynamic noise while spatial cues manipulate their attention. By adapting a reverse-correlation method from human studies, we linked behavioral decisions to stimulus features and locations. We show that mice deployed attention to a small rostral region of the visual field. Within this region, mice attended to multiple features (orientation, spatial frequency, contrast) that indicated the presence of weak vertical bars. This attentional tuning grew with training, multiplicatively scaled behavioral sensitivity, approached that of an ideal observer, and resembled the effects of attention in humans. Taken together, we demonstrate that mice can simultaneously attend to multiple features and locations of a visual stimulus.

Fourier Ptychographic Microscopic Reconstruction Method Based on Residual Hybrid Attention Network

Fourier ptychographic microscopy (FPM) is a novel technique for computing microimaging that allows imaging of samples such as pathology sections. However, due to the influence of systematic errors and noise, the quality of reconstructed images using FPM is often poor, and the reconstruction efficiency is low. In this paper, a hybrid attention network that combines spatial attention mechanisms with channel attention mechanisms into FPM reconstruction is introduced. Spatial attention can extract fine spatial features and reduce redundant features while, combined with residual channel attention, it adaptively readjusts the hierarchical features to achieve the conversion of low-resolution complex amplitude images to high-resolution ones. The high-resolution images generated by this method can be applied to medical cell recognition, segmentation, classification, and other related studies, providing a better foundation for relevant research.

Spatial attention modulates auditory dominance in audiovisual order judgment

Auditory dominance in audiovisual temporal order judgment is shown here to be modulated by exogenous orienting of attention to a spatial cue independent of the cue modality. The visual stimulus has to lead the auditory one further in advance for cued relative to uncued locations in order for the two to be perceived simultaneously, possibly suggesting an inhibitory function of spatial attention on temporal processing.

Erratum: Attentional capture by fearful faces requires consciousness and is modulated by task-relevancy: a dot-probe EEG study

[This corrects the article DOI: 10.3389/fnins.2023.1152220.].

Attention-Guided Instance Segmentation for Group-Raised Pigs

In the pig farming environment, complex factors such as pig adhesion, occlusion, and changes in body posture pose significant challenges for segmenting multiple target pigs. To address these challenges, this study collected video data using a horizontal angle of view and a non-fixed lens. Specifically, a total of 45 pigs aged 20-105 days in 8 pens were selected as research subjects, resulting in 1917 labeled images. These images were divided into 959 for training, 192 for validation, and 766 for testing. The grouped attention module was employed in the feature pyramid network to fuse the feature maps from deep and shallow layers. The grouped attention module consists of a channel attention branch and a spatial attention branch. The channel attention branch effectively models dependencies between channels to enhance feature mapping between related channels and improve semantic feature representation. The spatial attention branch establishes pixel-level dependencies by applying the response values of all pixels in a single-channel feature map to the target pixel. It further guides the original feature map to filter spatial location information and generate context-related outputs. The grouped attention, along with data augmentation strategies, was incorporated into the Mask R-CNN and Cascade Mask R-CNN task networks to explore their impact on pig segmentation. The experiments showed that introducing data augmentation strategies improved the segmentation performance of the model to a certain extent. Taking Mask-RCNN as an example, under the same experimental conditions, the introduction of data augmentation strategies resulted in improvements of 1.5%, 0.7%, 0.4%, and 0.5% in metrics AP⁵⁰, AP⁷⁵, AP^L, and AP, respectively. Furthermore, our grouped attention module achieved the best performance. For example, compared to the existing attention module CBAM, taking Mask R-CNN as an example, in terms of the metric AP⁵⁰, AP⁷⁵, AP^L, and AP, the grouped attention outperformed 1.0%, 0.3%, 1.1%, and 1.2%, respectively. We further studied the impact of the number of groups in the grouped attention on the final segmentation results. Additionally, visualizations of predictions on third-party data collected using a top-down data acquisition method, which was not involved in the model training, demonstrated that the proposed model in this paper still achieved good segmentation results, proving the transferability and robustness of the grouped attention. Through comprehensive analysis, we found that grouped attention is beneficial for achieving high-precision segmentation of individual pigs in different scenes, ages, and time periods. The research results can provide references for subsequent applications such as pig identification and behavior analysis in mobile settings.

Corrigendum: An initial prediction and fine-tuning model based on improving GCN for 3D human motion prediction

[This corrects the article DOI: 10.3389/fncom.2023.1145209.].

A feature and conjunction visual search immersive virtual reality serious game for measuring spatial and distractor inhibition attention using response time and action kinematics

BACKGROUND

Treisman (1980) proposed that visual-spatial attention to targets presented with distractors involves parallel and serial cognition. When the target is different from distractors by a single feature, the number of distractors does not influence search speed (parallel). However, when the target is different from the distractor by a conjunction of features, increased numbers of distractors increase task difficulty (serial). Here, we developed a serious game in immersive virtual reality (IVR) for evaluating spatial and distractor inhibition attention.

METHODS

We tested 60 healthy participants. They performed the serious game in which they had to find a target mole wearing a red miner's helmet. In the single feature parallel conditions, the distractor moles wore blue (miner's or horned) helmets, and in the conjunction feature serial conditions, the distractor moles wore blue miner's helmets or red horned helmets. There were 11-17-23 distractors. Responses were made with the dominant hand by hitting the target with a virtual hammer. We measured mean response time (RT), mean velocity (MV) and coefficient of variance of speed (CV).

RESULTS

Participants were significantly slower (RT and MV) and showed greater CV when responding to targets in conjunction compared to single feature search tasks. Further, participants were slower (RT and MV) and showed greater CV when the number of distractors increased. A significant interaction between search tasks and distractors showed that RT and CV only increased with distractor number for the conjunction search tasks. MV decreased with distractor number for both single and conjunction tasks, with a stronger decrease for conjunction relative to single feature search.

CONCLUSION

The results replicated previous findings, providing support for the use of immersive virtual reality technology for the simultaneous evaluation of spatial and distractor inhibition attention using complex 3D objects.

On the Use of a Convolutional Block Attention Module in Deep Learning-Based Human Activity Recognition with Motion Sensors

Sensor-based human activity recognition with wearable devices has captured the attention of researchers in the last decade. The possibility of collecting large sets of data from various sensors in different body parts, automatic feature extraction, and aiming to recognize more complex activities have led to a rapid increase in the use of deep learning models in the field. More recently, using attention-based models for dynamically fine-tuning the model features and, in turn, improving the model performance has been investigated. However, the impact of using channel, spatial, or combined attention methods of the convolutional block attention module (CBAM) on the high-performing DeepConvLSTM model, a hybrid model proposed for sensor-based human activity recognition, has yet to be studied. Additionally, since wearables have limited resources, analysing the parameter requirements of attention modules can serve as an indicator for optimizing resource consumption. In this study, we explored the performance of CBAM on the DeepConvLSTM architecture both in terms of recognition performance and the number of additional parameters required by attention modules. In this direction, the effect of channel and spatial attention, individually and in combination, were examined. To evaluate the model performance, the Pamap2 dataset containing 12 daily activities and the Opportunity dataset with its 18 micro activities were utilized. The results showed that the performance for Opportunity increased from 0.74 to 0.77 in the macro f1-score owing to spatial attention, while for Pamap2, the performance increased from 0.95 to 0.96 owing to the channel attention applied to DeepConvLSTM with a negligible number of additional parameters. Moreover, when the activity-based results were analysed, it was observed that the attention mechanism increased the performance of the activities with the worst performance in the baseline model without attention. We present a comparison with related studies that use the same datasets and show that we could achieve higher scores on both datasets by combining CBAM and DeepConvLSTM.

MAS-UNet: a U-shaped network for prostate segmentation

Prostate cancer is a common disease that seriously endangers the health of middle-aged and elderly men. MRI images are the gold standard for assessing the health status of the prostate region. Segmentation of the prostate region is of great significance for the diagnosis of prostate cancer. In the past, some methods have been used to segment the prostate region, but segmentation accuracy still has room for improvement. This study has proposed a new image segmentation model based on Attention UNet. The model improves Attention UNet by using GN instead of BN, adding dropout to prevent overfitting, introducing the ASPP module, adding channel attention to the attention gate module, and using different channels to output segmentation results of different prostate regions. Finally, we conducted comparative experiments using five existing UNet-based models, and used the dice coefficient as the metric to evaluate the segmentation result. The proposed model achieves dice scores of 0.807 and 0.907 in the transition region and the peripheral region, respectively. The experimental results show that the proposed model is better than other UNet-based models.

Spatial Attention Modulates Neuronal Interactions between Simple and Complex Cells in V1

Visual perception is profoundly modulated by spatial attention, which can selectively prioritize goal-related information. Previous studies found spatial attention facilitated the efficacy of neuronal communication between visual cortices with hierarchical organizations. In the primary visual cortex (V1), there is also a hierarchical connection between simple (S) and complex (C) cells. We wonder whether and how spatial attention modulates neuronal communication within V1, especially for neuronal pairs with heterogeneous visual input. We simultaneously recorded the pairs' activity from macaque monkeys when they performed a spatial-attention-involved task, then applied likelihood-based Granger causality analysis to explore attentional modulation of neuronal interactions. First, a significant attention-related decrease in Granger causality was found in S-C pairs, which primarily displayed in the S-to-C feedforward connection. Second, the interaction strength of the feedforward connection was significantly higher than that of the feedback under attend toward (AT) conditions. Although information flow did not alter as the attentional focus shifted, the strength of communications between target- and distractor-stimuli-covered neurons differed only when attending to complex cells' receptive fields (RFs). Furthermore, pairs' communications depended on the attentional modulation of neurons' firing rates. Our findings demonstrate spatial attention does not induce specific information flow but rather amplifies directed communication within V1.

Top-down control of the left visual field bias in cued visual spatial attention

A left visual field (LVF) bias in perceptual judgments, response speed, and discrimination accuracy has been reported in humans. Cognitive factors, such as visual spatial attention, are known to modulate or even eliminate this bias. We investigated this problem by recording pupillometry together with functional magnetic resonance imaging (fMRI) in a cued visual spatial attention task. We observed that (i) the pupil was significantly more dilated following attend-right than attend-left cues, (ii) the task performance (e.g. reaction time [RT]) did not differ between attend-left and attend-right trials, and (iii) the difference in cue-related pupil dilation between attend-left and attend-right trials was inversely related to the corresponding difference in RT. Neuroscientically, correlating the difference in cue-related pupil dilation with the corresponding cue-related fMRI difference yielded activations primarily in the right hemisphere, including the right intraparietal sulcus and the right ventrolateral prefrontal cortex. These results suggest that (i) there is an asymmetry in visual spatial attention control, with the rightward attention control being more effortful than the leftward attention control, (ii) this asymmetry underlies the reduction or the elimination of the LVF bias, and (iii) the components of the attentional control networks in the right hemisphere are likely part of the neural substrate of the observed asymmetry in attentional control.

Effects of gamma-aminobutyric acid on working memory and attention: A randomized, double-blinded, placebo-controlled, crossover trial

BACKGROUND

γ-Aminobutyric acid (GABA) is a primary inhibitory neurotransmitter that plays a significant role in the central nervous system. Studies on both animals and humans show that GABA has the pharmacological potential for reducing the impact of cognitive disorders, as well as enhancing cognitive functions and mood. However, its specific effects on human attention and working memory have not yet been extensively studied.

AIMS

In this randomized, double-blind, placebo-controlled, and crossover trial, we aimed to test whether the administration of 800 mg GABA, dissolved in a drink, acutely affected visual working memory (VWM) maintenance, as well as temporal and spatial attention in healthy adults.

METHODS

The participants were 32 young adults (16 females and 16 males). Working memory recall precision, spatial attention and temporal attention were measured by a delayed match-to-sample task, a visual search (VS) task and a speeded rapid serial visual presentation task, respectively. Participants completed two experimental sessions (GABA and Placebo) in randomized and counterbalanced order. In each session, 45 min after administration of the drink, they completed all three aforementioned cognitive tasks.

RESULTS

Linear mixed model analysis results showed that GABA increased VS time, compared to the placebo, but did not affect VS accuracy, temporal attention, nor VWM precision.

CONCLUSIONS

The results suggest that GABA increases VS time but does not affect temporal attention and memory, and that previously reported effects on cognition might rely on other functions.

A Deep Learning Approach for Dengue Fever Prediction in Malaysia Using LSTM with Spatial Attention

This research aims to predict dengue fever cases in Malaysia using machine learning techniques. A dataset consisting of weekly dengue cases at the state level in Malaysia from 2010 to 2016 was obtained from the Malaysia Open Data website and includes variables such as climate, geography, and demographics. Six different long short-term memory (LSTM) models were developed and compared for dengue prediction in Malaysia: LSTM, stacked LSTM (S-LSTM), LSTM with temporal attention (TA-LSTM), S-LSTM with temporal attention (STA-LSTM), LSTM with spatial attention (SA-LSTM), and S-LSTM with spatial attention (SSA-LSTM). The models were trained and evaluated on a dataset of monthly dengue cases in Malaysia from 2010 to 2016, with the task of predicting the number of dengue cases based on various climate, topographic, demographic, and land-use variables. The SSA-LSTM model, which used both stacked LSTM layers and spatial attention, performed the best, with an average root mean squared error (RMSE) of 3.17 across all lookback periods. When compared to three benchmark models (SVM, DT, ANN), the SSA-LSTM model had a significantly lower average RMSE. The SSA-LSTM model also performed well in different states in Malaysia, with RMSE values ranging from 2.91 to 4.55. When comparing temporal and spatial attention models, the spatial models generally performed better at predicting dengue cases. The SSA-LSTM model was also found to perform well at different prediction horizons, with the lowest RMSE at 4- and 5-month lookback periods. Overall, the results suggest that the SSA-LSTM model is effective at predicting dengue cases in Malaysia.

Hierarchical Bayesian perceptual template modeling of mechanisms of spatial attention in central and peripheral cuing

The external noise paradigm and perceptual template model (PTM) have successfully been applied to characterize observer properties and mechanisms of observer state changes (e.g. attention and perceptual learning) in several research domains, focusing on individual level analysis. In this study, we developed a new hierarchical Bayesian perceptual template model (HBPTM) to model the trial-by-trial data from all individuals and conditions in a published spatial cuing study within a single structure and compared its performance to that of a Bayesian Inference Procedure (BIP), which separately infers the posterior distributions of the model parameters for each individual subject without the hierarchical structure. The HBPTM allowed us to compute the joint posterior distribution of the hyperparameters and parameters at the population, observer, and experiment levels and make statistical inferences at all these levels. In addition, we ran a large simulation study that varied the number of observers and number of trials in each condition and demonstrated the advantage of the HBPTM over the BIP across all the simulated datasets. Although it is developed in the context of spatial attention, the HBPTM and its extensions can be used to model data from the external noise paradigm in other domains and enable predictions of human performance at both the population and individual levels.

Spatial attention based on 2D location and relative depth order modulates visual working memory in a 3D environment

The attentional effect on visual working memory (VWM) has been a heated research topic in the past two decades. Studies show that VWM performance for an attended memory item can be improved by cueing its two-dimensional (2D) spatial location during retention. However, few studies have investigated the effect of attentional selection on VWM in a three-dimensional setting, and it remains unknown whether depth information can produce beneficial attentional effects on 2D visual representations similar to 2D spatial information. Here we conducted four experiments, displaying memory items at various stereoscopic depth planes, and examined the retro-cue effects of four types of cues - a cue would either indicate the 2D or depth location of a memory item, and either in the form of physical (directly pointing to a location) or symbolic (numerically mapping onto a location) cues. We found that retro-cue benefits were only observed for cues directly pointing to a 2D location, whereas a null effect was observed for cues directly pointing to a depth location. However, there was a retro-cue effect when cueing the relative depth order, though the effect was weaker than that for cueing the 2D location. The selective effect on VWM based on 2D spatial attention is different from depth-based attention, and the divergence suggests that an object representation is primarily bound with its 2D spatial location, weakly bound with its depth order but not with its metric depth location. This indicates that attentional selection based on memory for depth, particularly metric depth, is ineffective.

A blinking focal pattern of re-entrant activity in the avian tectum

Re-entrant connections are inherent to nervous system organization; however, a comprehensive understanding of their operation is still lacking. In birds, topographically organized re-entrant signals, carried by axons from the nucleus-isthmi-parvocellularis (Ipc), are distinctly recorded as bursting discharges across the optic tectum (TeO). Here, we used up to 48 microelectrodes regularly spaced on the superficial tectal layers of anesthetized pigeons to characterize the spatial-temporal pattern of this axonal re-entrant activity in response to different visual stimulation. We found that a brief luminous spot triggered repetitive waves of bursting discharges that, appearing from initial sources, propagated horizontally to areas representing up to 28° of visual space, widely exceeding the area activated by the retinal fibers. In response to visual motion, successive burst waves started along and around the stimulated tectal path, tracking the stimulus in discontinuous steps. When two stimuli were presented, the burst-wave sources alternated between the activated tectal loci, as if only one source could be active at any given time. Because these re-entrant signals boost the retinal input to higher visual areas, their peculiar dynamics mimic a blinking "spotlight," similar to the internal searching mechanism classically used to explain spatial attention. Tectal re-entry from Ipc is thus highly structured and intrinsically discontinuous, and higher tectofugal areas, which lack retinotopic organization, will thus receive incoming visual activity in a sequential and piecemeal fashion. We anticipate that analogous re-entrant patterns, perhaps hidden in less bi-dimensionally organized topographies, may organize the flow of neural activity in other parts of the brain as well.