Threat-induced prosocial behavior: enhanced exogenous attention to protect others from harm.

As social animals, humans tend to voluntarily engage in pro-social behavior to prevent harm to others. However, to what extent prosocial behavior can be reflected at the level of less voluntary cognitive processes remains unclear. Here, we examined how threat to others modulates exogenous attention. Fifty-four participants performed an exogenous spatial cueing task where the participant's performance determined whether electric shocks would be delivered either to themselves or to their anonymous co-participant. Threat of shock to the co-participant elicited orienting and reorienting responses that were faster than in the safe condition and did not differ from performance when participants avoided shocks to themselves. This attentional improvement was not due to speed-accuracy trade off and was associated with arousal, i.e., increased pupil dilation in both threat conditions. Together, these findings suggest that pro-social behavior triggers automatic attentional processes which may be relevant for providing immediate help without relying on reflexive processes.

Prenatal affective cognitive training to reduce the risk of postpartum depression (PACT): study protocol for a randomized controlled trial.

BACKGROUND: Postpartum depression (PPD) affects 30-50% of women with a history of previous depression or bipolar disorder and 8% of women with no history of depression. Negative cognitive biases in the perception of infant cues and difficulties with emotion regulation are replicated risk factors. Current interventions focus on detecting and treating rather than preventing PPD. The aim of this randomized controlled intervention trial is therefore to investigate the potential prophylactic effects of prenatal affective cognitive training for pregnant women at heightened risk of PPD. METHODS: The study will enrol a total of 292 pregnant women: 146 at high risk and 146 at low risk of PPD. Participants undergo comprehensive assessments of affective cognitive processing, clinical depressive symptoms, and complete questionnaires at baseline. Based on the responses, pregnant women will be categorized as either at high or low risk of PPD. High-risk participants will be randomized to either prenatal affective cognitive training (PACT) or care as usual (CAU) immediately after the baseline testing. The PACT intervention is based on emerging evidence for efficacy of affective cognitive training approaches in depression, including cognitive bias modification, attention bias modification, mindfulness-inspired emotion regulation exercises, and working memory training. Participants randomised to PACT will complete five individual computerised and virtual reality-based training sessions over 5 weeks. The primary outcome is the difference between intervention arms in the incidence of PPD, assessed with an interview 6 months after birth. We will also assess the severity of depressive symptoms, rated weekly online during the first 6 weeks postpartum. DISCUSSION: The results will have implications for future early prophylactic interventions for pregnant women at heightened risk of PPD. If the PACT intervention reduces the incidence of PPD, it can become a feasible, non-invasive prophylactic strategy during pregnancy, with positive mental health implications for these women and their children. TRIAL REGISTRATION: ClinicalTrials.gov NCT06046456 registered 21-09-2023, updated 08-07-2024.

Using Attention-UNet Models to Predict Protein Contact Maps.

Proteins are essential to life, and understanding their intrinsic roles requires determining their structure. The field of proteomics has opened up new opportunities by applying deep learning algorithms to large databases of solved protein structures. With the availability of large data sets and advanced machine learning methods, the prediction of protein residue interactions has greatly improved. Protein contact maps provide empirical evidence of the interacting residue pairs within a protein sequence. Template-free protein structure prediction systems rely heavily on this information. This article proposes UNet-CON, an attention-integrated UNet architecture, trained to predict residue-residue contacts in protein sequences. With the predicted contacts being more accurate than state-of-the-art methods on the PDB25 test set, the model paves the way for the development of more powerful deep learning algorithms for predicting protein residue interactions.

Cross-attention enables deep learning on limited omics-imaging-clinical data of 130 lung cancer patients.

Deep-learning tools that extract prognostic factors derived from multi-omics data have recently contributed to individualized predictions of survival outcomes. However, the limited size of integrated omics-imaging-clinical datasets poses challenges. Here, we propose two biologically interpretable and robust deep-learning architectures for survival prediction of non-small cell lung cancer (NSCLC) patients, learning simultaneously from computed tomography (CT) scan images, gene expression data, and clinical information. The proposed models integrate patient-specific clinical, transcriptomic, and imaging data and incorporate Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome pathway information, adding biological knowledge within the learning process to extract prognostic gene biomarkers and molecular pathways. While both models accurately stratify patients in high- and low-risk groups when trained on a dataset of only 130 patients, introducing a cross-attention mechanism in a sparse autoencoder significantly improves the performance, highlighting tumor regions and NSCLC-related genes as potential biomarkers and thus offering a significant methodological advancement when learning from small imaging-omics-clinical samples.

Eye-tracking measurement of attention bias to social threat among youth: A replication and extension study.

Attentional bias to social threat cues has been linked to heightened anxiety and irritability in youth. Yet, inconsistent methodology has limited replication and led to mixed findings. The current study aims to 1) replicate and extend two previous pediatric studies demonstrating a relationship between negative affectivity and attentional bias to social threat and 2) examine the test-retest reliability of an eye-tracking paradigm among a subsample of youth. Attention allocation to negative versus non-negative emotional faces was measured using a free-viewing eye-tracking task among youth (N=185 total, 60% female, M age=13.10 years, SD age=2.77) with three face-pair conditions: happy-angry, neutral-disgust, sad-happy. Replicating procedures of two previous studies, linear mixed-effects models compared attention bias between children with anxiety disorders and healthy controls. Bifactor analysis was used to parse shared versus unique facets of general negative affectivity (i.e., anxiety, irritability), which were then examined in relation to attention bias. Test-retest reliability of the bias-index was estimated among a subsample of youth (N=36). No significant differences in attention allocation or bias emerged between anxiety and healthy control groups. While general negative affectivity across the sample was not associated with attention bias, there was a positive relationship for anxiety and irritability on duration of attention allocation toward negative faces. Test-retest reliability for attention bias was moderate (r=0.50, p<.01). While anxiety-related findings from the two previous studies were not replicated, the relationship between attention bias and facets of negative affect suggests a potential target for treatment. Evidence for test-retest reliability encourages future use of the eye-tracking task for researchers.

EEGGAN-Net: enhancing EEG signal classification through data augmentation.

Background: Emerging brain-computer interface (BCI) technology holds promising potential to enhance the quality of life for individuals with disabilities. Nevertheless, the constrained accuracy of electroencephalography (EEG) signal classification poses numerous hurdles in real-world applications. Methods: In response to this predicament, we introduce a novel EEG signal classification model termed EEGGAN-Net, leveraging a data augmentation framework. By incorporating Conditional Generative Adversarial Network (CGAN) data augmentation, a cropped training strategy and a Squeeze-and-Excitation (SE) attention mechanism, EEGGAN-Net adeptly assimilates crucial features from the data, consequently enhancing classification efficacy across diverse BCI tasks. Results: The EEGGAN-Net model exhibits notable performance metrics on the BCI Competition IV-2a and IV-2b datasets. Specifically, it achieves a classification accuracy of 81.3% with a kappa value of 0.751 on the IV-2a dataset, and a classification accuracy of 90.3% with a kappa value of 0.79 on the IV-2b dataset. Remarkably, these results surpass those of four other CNN-based decoding models. Conclusions: In conclusion, the amalgamation of data augmentation and attention mechanisms proves instrumental in acquiring generalized features from EEG signals, ultimately elevating the overall proficiency of EEG signal classification.

Art and mentalizing in early intervention psychosis: rationale and therapist insights on a new psychoeducational course.

In this paper, we explore the rationale for a combined art therapy and mentalization-based treatment (MBT) group course for those experiencing a first episode of psychosis (FEP). We discuss the theoretical background for how art and MBT theory can help us better understand and work with groups of individuals experiencing FEP, particularly focusing on avoidance and insecure attachment styles. We outline the delivery of a ten-week psychoeducational Art MBT course within an Early Intervention in Psychosis (EIP) Service and discuss our experiential insights into this new modality as co-therapists. We conclude by proposing that art therapy and mentalizing practice together offer an accessible, useful and practical group structure for EIP services, which could improve individuals' mentalizing capacity and overall social functioning.

The evolution of subjective cognition after meditation training in older people: a secondary analysis of the three-arm age-well randomized controlled trial.

Aging is associated with cognitive changes, even in the absence of brain pathology. This study aimed to determine if meditation training, by comparison to active and passive control groups, is linked to changes in the perception of cognitive functioning in older adults. One hundred thirty-four healthy older participants from the Age-Well Randomized Clinical Trial were included: 45 followed a meditation training, 45 a non-native language training and 44 had no intervention. Subjective cognition was assessed at baseline and following the 18-month intervention period. Perception of attentional efficiency was assessed using internal and external Attentional Style Questionnaire (ASQ) subscale scores. Perception of global cognitive capacities was measured via the total score of Cognitive Difficulties Scale (CDS). Deltas ([posttest minus pretest scores]/standard deviation at pretest) were calculated for the analyses. Generalized mixed effects models controlling for age, sex, education and baseline scores revealed that meditation training decreased the vulnerability score toward external distractors measured by the ASQ compared to non-native language training. However, no between-groups differences on ASQ internal or CDS total scores were observed. Results suggest a beneficial effect of meditation practice on perceived management of external distracting information in daily life. Meditation training may cultivate the ability to focus on specific information (e.g., breath) and ignore stimulation from other kinds of stimuli (e.g., noise).

The Role of Attention in Placebo and Nocebo Effects.

BACKGROUND: Although some existing models propose that attention may be crucially implicated in placebo/nocebo effects, empirical research on this aspect remains limited and scattered. PURPOSE: This systematic review aims to provide an inclusive overview of studies that have either directly manipulated or assessed attention within the context of placebo and nocebo procedures so to gain a synthetized picture of the role of this variable in placebo/nocebo effects. Importantly, only studies in which attention represented a mechanism or mediator of the placebo/nocebo response, and not a primary outcome, were included. METHODS: A systematic search was conducted across multiple databases, including PubMed, Scopus, PsycINFO, Web of Science, and Embase, to identify peer-reviewed studies. These studies were subjected to methodological evaluation and eligibility criteria for inclusion. RESULTS: We identified and classified 12 studies into three categories based on their focus: (i) those that directly assessed attention, (ii) those that directly manipulated participants' attention, and (iii) those that combined both a direct manipulation and assessment of attention. In all selected studies attention acted as a mechanism or mediator of the placebo/nocebo response, and was not considered a primary outcome of the placebo/nocebo manipulation. CONCLUSIONS: The synthesis of the included studies reveals that the role of attention in placebo and nocebo effects is still a topic of debate, marked by variations in how attention is conceptualized and measured. Results suggest that attention has significant clinical implications, particularly in optimizing therapeutic efficacy by directing patients' focus toward signs of healing and away from indicators of illness or distress. To advance our understanding, future research should explore these attentional mechanisms, in conjunction with neurophysiological correlates.

To date, empirical research on the role of attention in placebo/nocebo effects remains scarce and inconclusive. The aim of this systematic review is to offer an overview of studies that have either directly manipulated or assessed attention as a mechanism or mediator of placebo/nocebo responses. Peer-review studies were subjected to methodological evaluation and eligibility criteria, and 12 studies were selected and classified into 3 categories based on their focus: (i) those that directly assessed attention, (ii) those that directly manipulated participants' attention, and (iii) those that combined both a direct manipulation and assessment of attention. The synthesis of the included studies points to the nuanced methodological approaches to the study of the role of attention in placebo and nocebo effects, marked by variations in how this variable is conceptualized and measured. Overall, results support the idea that placebo/nocebo effects are not always a direct byproduct of expectations, with attention acting as an important factor to consider when exploring this relationship. Particularly, attention plays an important role in optimizing therapeutic efficacy by directing patients' focus toward signs of healing and away from indicators of illness or distress.

The association between infantile microcytic anemia and attention deficit hyperactivity disorder, a case-control study.

Background: Microcytic anemia due to iron deficiency is the most common type of anemia in children in Israel and many parts of the world, and has been shown to have negative consequences for the cognitive performance. We aimed to examine the association between microcytic anemia at age 9-18 months and ADHD during childhood. Methods: This case-control study included healthy children aged 6-18 years at data collection (April 2020), insured by Clalit-Health-Services, and aged 9-18 months between June 2004 and December 2013, when a blood-count was performed. The study group included children diagnosed with ADHD based on the medical documentation of at least two consecutive stimulant prescriptions. A control group without any stimulant prescriptions was matched in a ratio of 1-3:1, by year of birth, sex and cultural background. Any microcytic anemia was defined as Hb < 10.5 g/dl and MCV 60-75 fl. Moderate microcytic anemia as Hb 7-9.9 g/dl. We performed a conditional-logistic-regression analysis, adjusted by socioeconomic status (SES) and year of birth. Sensitivity analysis examined this association stratified by sex, cultural background, SES and age at data collection quintiles. Results: Any microcytic anemia prevalence was lower in the ADHD group (n = 19,467) as compared to the controls (n = 39,004) (3.4 % and 4.0 %, respectively), adjusted-OR = 0.86 (95%CI: 0.78, 0.98). The prevalence of moderate microcytic anemia was similar (0.9 % vs. 1.0 %). Lower any microcytic anemia prevalence in the ADHD group was found in boys, secular-traditional Jews, and in the 4th quintile of age (12.1-13.5 years). Conclusions: We found a small inverse association between microcytic anemia at 9-18-months and ADHD during childhood, thus rejecting our hypothesis that microcytic anemia at infancy is associated with a higher prevalence of ADHD. Further studies are warranted, to examine the effects of ID and brain iron concentration on the development of ADHD in childhood.

Perceptual decoupling in the sustained attention to response task is unlikely.

Researchers dispute the cause of errors in high Go, low No Go target detection tasks, like the Sustained Attention to Response Task (SART). Some researchers propose errors in the SART are due to perceptual decoupling, where a participant is unaware of stimulus identity. This lack of external awareness causes an erroneous response. Other researchers suggest the majority of the errors in the SART are instead due to response leniency, not perceptual decoupling. Response delays may enable a participant who is initially unaware of stimulus identity, perceptually decoupled, to become aware of stimulus identity, or perceptually recoupled. If, however, the stimulus presentation time is shortened to the minimum necessary for stimulus recognition and the stimulus is disrupted with a structured mask, then there should be no time to enable perception to recouple even with a response delay. From the perceptual decoupling perspective, there should be no impact of a response delay on performance in this case. Alternatively if response bias is critical, then even in this case a response delay may impact performance. In this study, we shortened stimulus presentation time and added a structured mask. We examined whether a response delay impacted performance in the SART and tasks where the SART's response format was reversed. We expected a response delay would only impact signal detection theory bias, c, in the SART, where response leniency is an issue. In the reverse formatted SART, since bias was not expected to be lenient, we expected no impact or minimal impact of a response delay on response bias. These predictions were verified. Response bias is more critical in understanding SART performance, than perceptual decoupling, which is rare if it occurs at all in the SART.

Confidence for intrusion errors during the attentional blink depends on target-defining features.

Research surrounding the attentional blink phenomenon - a deficit in responding to the second of two temporally proximal stimuli when presented 150-500 ms after the first - has used a wide variety of target-defining and response features of stimuli. The typical U-shape curve for absolute performance is robust, surviving across most stimulus features, and therefore changes in performance are discussed as dynamics in an attentional system that are nonspecific a stimulus type. However, the patterns of errors participants make might not show the same robustness, and participants' confidences in these errors might differ - potentially suggesting the involvement of different attentional or perceptual mechanisms. The present research is a comparison of error patterns and confidence in those errors when letter target stimuli are defined by either the color of the letter, the presence of a surrounding annulus, or the color of the annulus. Across three experiments, we show that participants erroneously report stimuli that are further away from T2 and they are similarly confident in specifically their post-target errors as their correct responses when annuli define targets, but not when color of the letter defines targets. Experiment 3 provides some evidence to suggest that this error pattern and associated confidence is time-dependent when the color of the annulus defines the target, but not when the color of the letter defines the target. These results raise questions concerning the nature of the errors and possibly the mechanisms of the attentional blink phenomenon itself.

Prenatal tobacco and tobacco-cannabis co-exposure: Relationship with attention and memory in middle childhood.

We examined associations between prenatal tobacco exposure (with and without cannabis exposure) and children's performance on laboratory measures of sustained attention, attentional set shifting, and working memory in middle childhood (9-12 years of child age). Participants were recruited in the first trimester of pregnancy and oversampled for prenatal tobacco exposure; with a smaller sample (n = 133; n = 34 non-substance exposed, n = 37 exposed to tobacco only, n = 62 co-exposed) invited (oversampled for co-exposure) to participate in the middle-childhood assessment (M age = 10.6, SD = 0.77; 68% Black, 20% Hispanic). Results for sustained attention indicated lower attention (percent hits) at the first epoch for tobacco only exposed compared to non-exposed and co-exposed; a trend (p = .07) towards increases in impulsive responding across time (a total of 8 epochs) for tobacco exposed (with and without cannabis) compared to non-exposed children; and a significant association between higher number of cigarettes in the first trimester and greater increases in impulsive responding across epochs. However, children prenatally exposed to tobacco (with and without cannabis) demonstrated greater short-term memory compared to children not prenatally exposed, and this difference was driven by higher scores for children prenatally co-exposed to tobacco and cannabis compared to those who were non-exposed. Overall, results suggest that prenatal tobacco exposure, especially in the first trimester, may increase risk for impulsive responding on tasks requiring sustained attention, and that co-use of cannabis did not exacerbate these associations. The higher short-term memory scores among children who were co-exposed compared to non-exposed are perplexing and need replication, particularly in studies with larger sample sizes and samples exposed only to cannabis to examine this more closely.

Contrastive cross-domain sequential recommendation via emphasized intention features.

The objective of cross-domain sequential recommendation is to forecast upcoming interactions by leveraging past interactions across diverse domains. Most methods aim to utilize single-domain and cross-domain information as much as possible for personalized preference extraction and effective integration. However, on one hand, most models ignore that cross-domain information is composed of multiple single-domains when generating representations. They still treat cross-domain information the same way as single-domain information, resulting in noisy representation generation. Only by imposing certain constraints on cross-domain information during representation generation can subsequent models minimize interference when considering user preferences. On the other hand, some methods neglect the joint consideration of users' long-term and short-term preferences and reduce the weight of cross-domain user preferences to minimize noise interference. To better consider the mutual promotion of cross-domain and single-domains factors, we propose a novel model (C2DREIF) that utilizes Gaussian graph encoders to handle information, effectively constraining the correlation of information and capturing useful contextual information more accurately. It also employs a Top-down transformer to accurately extract user intents within each domain, taking into account the user's long-term and short-term preferences. Additionally, entropy regularized is applied to enhance contrastive learning and mitigate the impact of randomness caused by negative sample composition.

EGPDI: identifying protein-DNA binding sites based on multi-view graph embedding fusion.

Mechanisms of protein-DNA interactions are involved in a wide range of biological activities and processes. Accurately identifying binding sites between proteins and DNA is crucial for analyzing genetic material, exploring protein functions, and designing novel drugs. In recent years, several computational methods have been proposed as alternatives to time-consuming and expensive traditional experiments. However, accurately predicting protein-DNA binding sites still remains a challenge. Existing computational methods often rely on handcrafted features and a single-model architecture, leaving room for improvement. We propose a novel computational method, called EGPDI, based on multi-view graph embedding fusion. This approach involves the integration of Equivariant Graph Neural Networks (EGNN) and Graph Convolutional Networks II (GCNII), independently configured to profoundly mine the global and local node embedding representations. An advanced gated multi-head attention mechanism is subsequently employed to capture the attention weights of the dual embedding representations, thereby facilitating the integration of node features. Besides, extra node features from protein language models are introduced to provide more structural information. To our knowledge, this is the first time that multi-view graph embedding fusion has been applied to the task of protein-DNA binding site prediction. The results of five-fold cross-validation and independent testing demonstrate that EGPDI outperforms state-of-the-art methods. Further comparative experiments and case studies also verify the superiority and generalization ability of EGPDI.

Plant leaf disease recognition based on improved SinGAN and improved ResNet34.

The identification of plant leaf diseases is crucial in precision agriculture, playing a pivotal role in advancing the modernization of agriculture. Timely detection and diagnosis of leaf diseases for preventive measures significantly contribute to enhancing both the quantity and quality of agricultural products, thereby fostering the in-depth development of precision agriculture. However, despite the rapid development of research on plant leaf disease identification, it still faces challenges such as insufficient agricultural datasets and the problem of deep learning-based disease identification models having numerous training parameters and insufficient accuracy. This paper proposes a plant leaf disease identification method based on improved SinGAN and improved ResNet34 to address the aforementioned issues. Firstly, an improved SinGAN called Reconstruction-Based Single Image Generation Network (ReSinGN) is proposed for image enhancement. This network accelerates model training speed by using an autoencoder to replace the GAN in the SinGAN and incorporates a Convolutional Block Attention Module (CBAM) into the autoencoder to more accurately capture important features and structural information in the images. Random pixel Shuffling are introduced in ReSinGN to enable the model to learn richer data representations, further enhancing the quality of generated images. Secondly, an improved ResNet34 is proposed for plant leaf disease identification. This involves adding CBAM modules to the ResNet34 to alleviate the limitations of parameter sharing, replacing the ReLU activation function with LeakyReLU activation function to address the problem of neuron death, and utilizing transfer learning-based training methods to accelerate network training speed. This paper takes tomato leaf diseases as the experimental subject, and the experimental results demonstrate that: (1) ReSinGN generates high-quality images at least 44.6 times faster in training speed compared to SinGAN. (2) The Tenengrad score of images generated by the ReSinGN model is 67.3, which is improved by 30.2 compared to the SinGAN, resulting in clearer images. (3) ReSinGN model with random pixel Shuffling outperforms SinGAN in both image clarity and distortion, achieving the optimal balance between image clarity and distortion. (4) The improved ResNet34 achieved an average recognition accuracy, recognition precision, recognition accuracy (redundant as it's similar to precision), recall, and F1 score of 98.57, 96.57, 98.68, 97.7, and 98.17%, respectively, for tomato leaf disease identification. Compared to the original ResNet34, this represents enhancements of 3.65, 4.66, 0.88, 4.1, and 2.47%, respectively.

Virtual reality in functional neurological disorder: a theoretical framework and research agenda for use in the real world.

Functional neurological disorder (FND) is a common and disabling condition at the intersection of neurology and psychiatry. Despite remarkable progress over recent decades, the mechanisms of FND are still poorly understood and there are limited diagnostic tools and effective treatments. One potentially promising treatment modality for FND is virtual reality (VR), which has been increasingly applied to a broad range of conditions, including neuropsychiatric disorders. FND has unique features, many of which suggest the particular relevance for, and potential efficacy of, VR in both better understanding and managing the disorder. In this review, we describe how VR might be leveraged in the treatment and diagnosis of FND (with a primary focus on motor FND and persistent perceptual-postural dizziness given their prominence in the literature), as well as the elucidation of neurocognitive mechanisms and symptom phenomenology. First, we review what has been published to date on the applications of VR in FND and related neuropsychiatric disorders. We then discuss the hypothesised mechanism(s) underlying FND, focusing on the features that are most relevant to VR applications. Finally, we discuss the potential of VR in (1) advancing mechanistic understanding, focusing specifically on sense of agency, attention and suggestibility, (2) overcoming diagnostic challenges and (3) developing novel treatment modalities. This review aims to develop a theoretical foundation and research agenda for the use of VR in FND that might be applicable or adaptable to other related disorders.

Identifying Autistic-Like Symptoms in Children with ADHD: A Comparative Study Using ADOS-2.

Purpose: Recent literature has focused attention on the presence of autistic-like symptoms in children with Attention Deficit/Hyperactivity Disorder (ADHD), who often exhibit social difficulties, posing challenges for a distinct clinical diagnosis. The current study aimed to identify the specific pattern of autistic symptoms in subjects with ADHD or Autistic Spectrum Disorder (ASD), examining similarities or differences at both the domain and individual item levels. Patients and Methods: In this study, we enrolled 43 school-age children divided into the following: the ADHD group (n=25) consisted of children initially referred for ASD symptoms but subsequently clinically diagnosed with ADHD, and the ASD group consisted of 18 children with ASD. We used the Autism Diagnostic Observation Schedule, 2nd edition (ADOS-2), to examine relative differences in the presence of symptoms such as deficits in communication and social interaction, and restricted and repetitive behaviors in these two groups. Comparison between groups was conducted to explore differences in IQ, age, ADOS-2 domains, and externalizing and internalizing problems among the groups. Results: We found significant differences between the groups when comparing summary scores of ADOS-2 domains (Social Affect, Restricted and Repetitive Behavior, and Total Score). Interestingly, at the individual item level, the ADHD group exhibited a similar level of atypical behaviors compared to the ASD group in two items related to the social-communication area: "Pointing" and "Gestures". Additionally, the frequencies of "Stereotyped/idiosyncratic words or phrases", "Mannerisms", and "Repetitive interests and behaviors" also showed similarities between groups. Conclusion: These findings indicate the importance of exploring and developing potential transdiagnostic domains that could be targeted for treatments specifically designed for children with ADHD.

Growing evidence of pharmacotherapy effectiveness in managing attention-deficit/hyperactivity disorder in young children with or without autism spectrum disorder: a minireview.

Many children with autism spectrum disorder (ASD) also have attention-deficit/hyperactivity disorder (ADHD). ADHD in children is associated with increased risk of negative outcomes, and early intervention is critical. Current guidelines recommend psychosocial interventions such as behavioral training as the first line of therapy in managing ADHD symptoms in children with or without ASD. Where symptoms are refractory to these interventions, medications such as stimulants, α2-adrenergic agonist inhibitors, selective norepinephrine reuptake inhibitors, and second-generation antipsychotics are recommended. However, these pharmacotherapies do not have regulatory approval for use in children of preschool age, and evidence on their safety and efficacy in this population has historically been very limited. Since publication of the current guidelines in 2020, several new randomized controlled trials and real-world studies have been published that have investigated the efficacy and tolerability of these medications in preschool children with ADHD, with or without comorbid ASD. Here, we provide a review of the key findings of these studies, which suggest that there is growing evidence to support the use of pharmacological interventions in the management of ADHD in preschool children with comorbid ASD.

Acute Effects of Light during Daytime on Central Aspects of Attention and Affect:A Systematic Review.

Light regulates both image- and various non-image forming responses in humans, including acute effects on attention and affect. To advance the understanding of light's immediate effects, this systematic review describes the acute effects of monochromatic/narrow bandwidth and polychromatic white light during daytime on distinct aspects of attention (alertness, sustained attention, working memory, attentional control and flexibility), and measures of affect (self-report measures, performance-based tests, psychophysiological measures) in healthy, adult human subjects. Original, peer-reviewed (quasi-) experimental studies published between 2000 and May 2024 were included according to predefined inclusion and exclusion criteria. Study quality was assessed, and results were synthesized across aspects of attention and affect and grouped according to light interventions; monochromatic/narrowband-width or polychromatic white light (regular white, bright white, and white with high correlated color temperature (CCT)). Results from included studies (n = 62) showed that alertness and working memory were most affected by light. Electroencephalographic markers of alertness improved the most with exposure to narrow bandwidth long-wavelength light, regular white, and white light with high CCT. Self-reported alertness and measures of working memory improved the most with bright white light. Results from studies testing the acute effects on sustained attention and attentional control and flexibility were inconclusive. Performance-based and psychophysiological measures of affect were only influenced by narrow bandwidth long-wavelength light. Polychromatic white light exerted mixed effects on self-reported affect. Studies were strongly heterogeneous in terms of light stimuli characteristics and reporting of light stimuli and control of variables influencing light's acute effects.