Detecting mental and physical disorders using multi-task learning equipped with knowledge graph attention network.

Mental and physical disorders (MPD) are inextricably linked in many medical cases; psychosomatic diseases can be induced by mental concerns and psychological discomfort can ensue from physiological diseases. However, existing medical informatics studies focus on identifying mental or physical disorders from a unilateral perspective. Consequently, no existing domain knowledge base, corpus, or detection modeling approach considers mental as well as physical aspects concurrently. This paper proposes a joint modeling approach to detect MPD. First, we crawl through online medical consultation records of patients from websites and build an MPD knowledge ontology by extracting the core conceptual features of the text. Based on the ontology, an MPD knowledge graph containing 12,673 nodes and 82,195 relations is obtained using term matching with a domain thesaurus of each concept. Subsequently, an MPD corpus with fine-grained severities (None, Mild, Moderate, Severe, Dangerous) and 8909 records is constructed by formulating MPD classification criteria and a data annotation process under the guidance of domain experts. Taking the knowledge graph and corpus as the dataset, we design a multi-task learning model to detect the MPD severity, in which a knowledge graph attention network (KGAT) is embedded to better extract knowledge features. Experiments are performed to demonstrate the effectiveness of our model. Furthermore, we employ ontology-based and centrality-based methods to discover additional potential inferred knowledge, which can be captured by KGAT so as to improve the prediction performance and interpretability of our model. Our dataset has been made publicly available, so it can be further used as a medical informatics reference in the fields of psychosomatic medicine, psychiatrics, physical co-morbidity, and so on.

Down-regulation of theta amplitude through neurofeedback improves executive control network efficiency in healthy children.

Despite extensive clinical research on neurofeedback (NF) in attention-deficit/hyperactivity disorder (ADHD), few studies targeted the optimization of attention performance in healthy children. As a crucial component of attention networks, the executive control network, involved in resolving response conflicts and allocating cognitive resources, is closely linked to theta activity. Here, we aimed to answer whether theta down-regulating NF can enhance healthy children's attention performance, especially the executive control network. Sixty children aged 6-12 years were randomly assigned to the NF and waitlist control groups. The NF group received theta down-regulation NF training for five days (a total of 100 mins), and the attention performance of both groups was measured by the attention network test (ANT) in the pre, post-NF, and 7-day follow-up. The electroencephalographic (EEG) results demonstrated a significant decrease in resting-state theta amplitude within sessions. For the behavioral results, the NF group exhibited significant improvements in overall attention performance and the efficiency of the executive control network relative to the control group in the post-NF and follow-up assessment, whereas the alerting and orienting networks remained unchanged. These findings proved the feasibility of theta down-regulating NF and its positive effect on attention in the healthy children population. In particular, the facilitation of the efficiency of the executive control network and the unaltered performance of the other two attention networks in the NF group may support the causality between theta rhythm and the executive control network.

Effect of Meditation on Brain Activity during an Attention Task: A Comparison Study of ASL and BOLD Task fMRI.

Focused attention meditation (FAM) training has been shown to improve attention, but the neural basis of FAM on attention has not been thoroughly understood. Here, we aim to investigate the neural effect of a 2-month FAM training on novice meditators in a visual oddball task (a frequently adopted task to evaluate attention), evaluated with both ASL and BOLD fMRI. Using ASL, activation was increased in the middle cingulate (part of the salience network, SN) and temporoparietal (part of the frontoparietal network, FPN) regions; the FAM practice time was negatively associated with the longitudinal changes in activation in the medial prefrontal (part of the default mode network, DMN) and middle frontal (part of the FPN) regions. Using BOLD, the FAM practice time was positively associated with the longitudinal changes of activation in the inferior parietal (part of the dorsal attention network, DAN), dorsolateral prefrontal (part of the FPN), and precentral (part of the DAN) regions. The effect sizes for the activation changes and their association with practice time using ASL are significantly larger than those using BOLD. Our study suggests that FAM training may improve attention via modulation of the DMN, DAN, SN, and FPN, and ASL may be a sensitive tool to study the FAM effect on attention.

The relationship between attention networks and individual differences in visual mental imagery vividness - An EEG study.

Previous research has established a strong link between attention and visual mental imagery, but it's remained uncertain whether attention networks influence individual differences in the vividness of visual mental imagery. In our study, we examined 140 participants, assessing the vividness of imagery using the Vividness of Visual Imagery Questionnaire in both eyes-open and eyes-closed conditions. We employed the Attention Network Test, coupled with EEG recording, to characterize three attention sub-networks: alerting, orienting, and executive control. To pinpoint the specific attentional networks associated with the vividness of visual mental imagery, we utilized latent profile analysis to categorize participants into distinct subgroups. Additionally, we constructed a regression mixture model to explore how attention networks predict different latent categories of visual imagery vividness. Our findings revealed that the efficiency of the alerting network, as indicated by the N1 component, demonstrated a positive correlation with the vividness of visual imagery. This electrophysiological evidence underscores the role of the alerting network in shaping individual differences in the vividness of visual mental imagery.

Graph Attention Network based mapping of knowledge relations between chemical spaces of Nuclear factor kappa B and Centella asiatica.

The confounding nature of the innate immunity target Nuclear Factor kappa B (NF-κB) and its interaction with Centella asiatica (CA) molecules necessitate the intervention of advanced technologies, such as deep learning methods. The integration of chemical space concepts with deep learning technologies is a new way of knowledge mapping used to explore drug-target interactions, especially in molecular libraries derived from traditional medicine based molecular sources. The current constraint of virtual screening for mechanistic target hunting is the use of a binary classification model that includes active and inactive molecules from in vitro experiments to explore drug-target interaction. This study aims to explore the regulatory nature of the molecules from the inhibition and activation of the NF-κB bioassay data set and map this information for a knowledge-based analysis against the molecules of CA, a low-growing tropical plant. This finding has led to a new direction in the field, transitioning from the conventional active-inactive framework to a more comprehensive active-inactive-regulatory model. This approach can be thoroughly explored by leveraging a graph-based deep learning system. The study presents an innovative approach using a Graph Attention Network (GAT) to rank CA molecules in chemical space based on their similarity with NF-κB bioassay molecules, enabling the efficient analysis of complex relationships between molecules and their regulatory function. Graph Attention Network (GAT) overcomes the limitations of traditional deep learning models such as Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) in handling non-Euclidean graph data and allows for a more precise understanding of similarity ranking by utilizing molecular graphs and attention behavior. By measuring similarity and arranging a matrix of similarity ranking based on GAT, deep neural ranking-based algorithms confirmed the regulatory behaviour of an innate immunity target NF-κB with the support of underlying inverse mapping in the surjective chemical spaces of NF-κB bioassays and CA molecular spaces. Overall, the study introduces new techniques for exploring the regulatory behaviour of complex targets like NF-κB. We then used t-SNE for clustering in chemical space and scaffold hunting for scaffold property analysis and identified nine CA molecules that exhibit regulatory behavior of NF-κB target and are recommended for further investigation.

A hierarchical multilabel graph attention network method to predict the deterioration paths of chronic hepatitis B patients.

OBJECTIVE: Estimating the deterioration paths of chronic hepatitis B (CHB) patients is critical for physicians' decisions and patient management. A novel, hierarchical multilabel graph attention-based method aims to predict patient deterioration paths more effectively. Applied to a CHB patient data set, it offers strong predictive utilities and clinical value. MATERIALS AND METHODS: The proposed method incorporates patients' responses to medications, diagnosis event sequences, and outcome dependencies to estimate deterioration paths. From the electronic health records maintained by a major healthcare organization in Taiwan, we collect clinical data about 177 959 patients diagnosed with hepatitis B virus infection. We use this sample to evaluate the proposed method's predictive efficacy relative to 9 existing methods, as measured by precision, recall, F-measure, and area under the curve (AUC). RESULTS: We use 20% of the sample as holdouts to test each method's prediction performance. The results indicate that our method consistently and significantly outperforms all benchmark methods. It attains the highest AUC, with a 4.8% improvement over the best-performing benchmark, as well as 20.9% and 11.4% improvements in precision and F-measures, respectively. The comparative results demonstrate that our method is more effective for predicting CHB patients' deterioration paths than existing predictive methods. DISCUSSION AND CONCLUSION: The proposed method underscores the value of patient-medication interactions, temporal sequential patterns of distinct diagnosis, and patient outcome dependencies for capturing dynamics that underpin patient deterioration over time. Its efficacious estimates grant physicians a more holistic view of patient progressions and can enhance their clinical decision-making and patient management.

Modulation of pulvinar connectivity with cortical areas in the control of selective visual attention.

Selective attention mechanisms operate across large-scale cortical networks by amplifying behaviorally relevant sensory information while suppressing interference from distractors. Although it is known that fronto-parietal regions convey information about attentional priorities, it is unclear how such cortical communication is orchestrated. Based on its unique connectivity pattern with the cortex, we hypothesized that the pulvinar, a nucleus of the thalamus, may play a key role in coordinating and modulating remote cortical activity during selective attention. By using a visual task that orthogonally manipulated top-down selection and bottom-up competition during functional MRI, we investigated the modulations induced by task-relevant (spatial cue) and task-irrelevant but salient (distractor) stimuli on functional interactions between the pulvinar, occipito-temporal cortex, and frontoparietal areas involved in selective attention. Pulvinar activity and connectivity were distinctively modulated during the co-occurrence of the cue and salient distractor stimuli, as opposed to the presence of one of these factors alone. Causal modelling analysis further indicated that the pulvinar acted by weighting excitatory signals to cortical areas, predominantly in the presence of both the cue and the distractor. These results converge to support a pivotal role of the pulvinar in integrating top-down and bottom-up signals among distributed networks when confronted with conflicting visual stimuli, and thus contributing to shape priority maps for the guidance of attention.

The Longitudinal Effect of Meditation on Resting-State Functional Connectivity Using Dynamic Arterial Spin Labeling: A Feasibility Study.

We aimed to assess whether dynamic arterial spin labeling (dASL), a novel quantitative MRI technique with minimal contamination of subject motion and physiological noises, could detect the longitudinal effect of focused attention meditation (FAM) on resting-state functional connectivity (rsFC). A total of 10 novice meditators who recorded their FAM practice time were scanned at baseline and at the 2-month follow-up. Two-month meditation practice caused significantly increased rsFC between the left medial temporal (LMT) seed and precuneus area and between the right frontal eye (RFE) seed and medial prefrontal cortex. Meditation practice time was found to be positively associated with longitudinal changes of rsFC between the default mode network (DMN) and dorsal attention network (DAN), between DMN and insula, and between DAN and the frontoparietal control network (FPN) but negatively associated with changes of rsFC between DMN and FPN, and between DAN and visual regions. These findings demonstrate the capability of dASL in identifying the FAM-induced rsFC changes and suggest that the practice of FAM can strengthen the efficient control of FPN on fast switching between DMN and DAN and enhance the utilization of attentional resources with reduced focus on visual processing.

Development of thalamus mediates paternal age effect on offspring reading: A preliminary investigation.

The importance of (inherited) genetic impact in reading development is well established. De novo mutation is another important contributor that is recently gathering interest as a major liability of neurodevelopmental disorders, but has been neglected in reading research to date. Paternal age at childbirth (PatAGE) is known as the most prominent risk factor for de novo mutation, which has been repeatedly shown by molecular genetic studies. As one of the first efforts, we performed a preliminary investigation of the relationship between PatAGE, offspring's reading, and brain structure in a longitudinal neuroimaging study following 51 children from kindergarten through third grade. The results showed that greater PatAGE was significantly associated with worse reading, explaining an additional 9.5% of the variance after controlling for a number of confounds-including familial factors and cognitive-linguistic reading precursors. Moreover, this effect was mediated by volumetric maturation of the left posterior thalamus from ages 5 to 8. Complementary analyses indicated the PatAGE-related thalamic region was most likely located in the pulvinar nuclei and related to the dorsal attention network by using brain atlases, public datasets, and offspring's diffusion imaging data. Altogether, these findings provide novel insights into neurocognitive mechanisms underlying the PatAGE effect on reading acquisition during its earliest phase and suggest promising areas of future research.

Closed-Loop Neurofeedback of α Synchrony during Goal-Directed Attention.

α Oscillations in sensory cortex, under frontal control, desynchronize during attentive preparation. Here, in a selective attention study with simultaneous EEG in humans of either sex, we first demonstrate that diminished anticipatory α synchrony between the mid-frontal region of the dorsal attention network and ventral visual sensory cortex [frontal-sensory synchrony (FSS)] significantly correlates with greater task performance. Then, in a double-blind, randomized controlled study in healthy adults, we implement closed-loop neurofeedback (NF) of the anticipatory α FSS signal over 10 d of training. We refer to this closed-loop experimental approach of rapid NF integrated within a cognitive task as cognitive NF (cNF). We show that cNF results in significant trial-by-trial modulation of the anticipatory α FSS measure during training, concomitant plasticity of stimulus-evoked α/θ responses, as well as transfer of benefits to response time (RT) improvements on a standard test of sustained attention. In a third study, we implement cNF training in children with attention deficit hyperactivity disorder (ADHD), replicating trial-by-trial modulation of the anticipatory α FSS signal as well as significant improvement of sustained attention RTs. These first findings demonstrate the basic mechanisms and translational utility of rapid cognitive-task-integrated NF.SIGNIFICANCE STATEMENT When humans prepare to attend to incoming sensory information, neural oscillations in the α band (8-14 Hz) undergo desynchronization under the control of prefrontal cortex. Here, in an attention study with electroencephalography, we first show that frontal-sensory synchrony (FSS) of α oscillations during attentive preparation significantly correlates with task performance. Then, in a randomized controlled study in healthy adults, we show that neurofeedback (NF) training of this α FSS signal within the attention task is feasible. We show that this rapid cognitive NF (cNF) approach engenders plasticity of stimulus-evoked neural responses, and improves performance on a standard test of sustained attention. In a final study, we implement cNF in children with attention deficit hyperactivity disorder (ADHD), replicating the improvement of sustained attention found in adults.

Attention and Default Mode Network Assessments of Meditation Experience during Active Cognition and Rest.

Meditation experience has previously been shown to improve performance on behavioral assessments of attention, but the neural bases of this improvement are unknown. Two prominent, strongly competing networks exist in the human cortex: a dorsal attention network, that is activated during focused attention, and a default mode network, that is suppressed during attentionally demanding tasks. Prior studies suggest that strong anti-correlations between these networks indicate good brain health. In addition, a third network, a ventral attention network, serves as a "circuit-breaker" that transiently disrupts and redirects focused attention to permit salient stimuli to capture attention. Here, we used functional magnetic resonance imaging to contrast cortical network activation between experienced focused attention Vipassana meditators and matched controls. Participants performed two attention tasks during scanning: a sustained attention task and an attention-capture task. Meditators demonstrated increased magnitude of differential activation in the dorsal attention vs. default mode network in a sustained attention task, relative to controls. In contrast, there were no evident attention network differences between meditators and controls in an attentional reorienting paradigm. A resting state functional connectivity analysis revealed a greater magnitude of anticorrelation between dorsal attention and default mode networks in the meditators as compared to both our local control group and a n = 168 Human Connectome Project dataset. These results demonstrate, with both task- and rest-based fMRI data, increased stability in sustained attention processes without an associated attentional capture cost in meditators. Task and resting-state results, which revealed stronger anticorrelations between dorsal attention and default mode networks in experienced mediators than in controls, are consistent with a brain health benefit of long-term meditation practice.

Changes in attentional processing following neurofeedback in patients with persistent post-concussive symptoms: a pilot study.

OBJECTIVE: Persistent post-concussive symptoms (PPCS) often include attention deficits, particularly orienting and executive attention. Research in other clinical populations has demonstrated that neurofeedback therapy (NFT) is effective at improving orienting and executive attention, although its effects on attentional networks in patients with PPCS are unknown. METHOD: In this single-group pilot study, we examined attention-related event-related potentials (ERPs) - N1 and P3 - and cognitive outcomes following Live Z-score training (LZT), a variant of NFT. RESULTS: No changes in early selective attention, as indexed by N1 amplitude, were observed; however, P3 amplitude, which indexes neural resource allocation, increased following LZT and returned to baseline by 3 months. Cognitive performance improved following treatment, which was sustained at 3 months. The magnitude of change in P3 and ANT performance did not differ between orienting or executive attention, suggesting LZT improved general attentional processing efficiency. CONCLUSION: Our results suggest that LZT may positively affect attention globally, but does not target specific attention networks. These pilot data warrant the initiation of a clinical trial evaluating the effectiveness of LZT for treating attention deficits in patients with PPCS.

Functional connectivity associated with five different categories of Autonomous Sensory Meridian Response (ASMR) triggers.

Autonomous sensory meridian response (ASMR) is a sensory-emotional phenomenon in which specific sensory stimuli ("ASMR triggers") reliably elicit feelings of relaxation and tingling sensations on the head, neck, and shoulders. However, there are individual differences in which stimuli elicit ASMR and in the intensity of these responses. In the current research, we used resting-state fMRI to examine the functional connectivity associated with these differences. Fifteen individuals with self-reported ASMR completed the ASMR Checklist, which measures sensitivity to different ASMR triggers, and a resting-state fMRI scan. Checklist scores were entered as covariates to determine whether the functional connectivity of eight resting-state networks differed as a function of participants' sensitivity to five categories of triggers. The results indicated unique patterns of functional connectivity associated with sensitivity to each ASMR trigger category. Sensitivity to two trigger categories was positively correlated with the dorsal attention network, suggesting that ASMR may involve atypical attentional processing.

Effects of a mindfulness-based intervention on cancer-related cognitive impairment: Results of a randomized controlled functional magnetic resonance imaging pilot study.

BACKGROUND: Many breast cancer survivors suffer from cognitive complaints after cancer treatment, affecting their quality of life. The objective of this pilot study was to investigate the effect of a blended-care mindfulness-based intervention (MBI) on chemotherapy-related cognitive impairment and functional brain changes. Furthermore, correlations between changes in cognitive functioning and self-reported behavioral factors were investigated. METHODS: Breast cancer survivors (n = 33) who reported cognitive impairment were randomly allocated to a mindfulness condition (n = 18) or a waitlist control condition (n = 15). Patients completed questionnaires on cognitive impairment, emotional distress, and fatigue; neuropsychological tests; and resting-state functional magnetic resonance imaging before the start of MBI (time 1 [T1]), immediately after the completion of an 8-week MBI program (T2), and 3 months postintervention (T3). Resting-state functional connectivity was estimated in the default mode network, the dorsal and salience attention networks, and the frontoparietal network. Mixed model repeated-measures analysis was performed to test the intervention effect. RESULTS: Patients in the mindfulness condition exhibited significantly higher connectivity between the dorsal and salience attention networks after the mindfulness intervention compared with those in the control condition. MBI participants also had reduced subjective cognitive impairment, emotional distress, and fatigue. No intervention effect was observed on neurocognitive tests. CONCLUSIONS: MBI may induce functional brain changes in networks related to attention and may have a positive effect on subjective measures of cognitive impairment in breast cancer survivors. Therefore, MBI could be a suitable intervention to improve quality of life in this population and deserves further study in this context.

Attention in Children With Autism Spectrum Disorder and the Effects of a Mindfulness-Based Program.

Objective: Children with autism spectrum disorder (ASD) show atypical attention. Mindfulness-based programs (MBPs), with self-regulation of attention as a basic component, could benefit these children. Method: We investigated how 49 children with ASD differed from 51 typically developing (TD) children in their attention systems; and whether their attention systems were improved by an MBP for children and their parents (MYmind), using a cognitive measure of attention, the Attention Network Test. Results: Children with ASD did not differ from TD children in the speed of the attention systems, but were somewhat less accurate in their orienting and executive attention. Also, MYmind did not significantly improve attention, although trend effects indicated improved orienting and executive attention. Robustness checks supported these improvements. Conclusion: Trend effects of the MBP on the attention systems of children with ASD were revealed, as well as minor differences between children with ASD and TD children in their attention systems.

Search asymmetry in a serial auditory task: Neural source analyses of EEG implicate attention strategies.

Here we report a detailed analysis of the fast network dynamics underlying P3a and P3b event-related potential (ERP) subcomponents generated during an unconventional serial auditory search paradigm. We dissect the electroencephalographic (EEG) data from an earlier study of ours, using a variety of advanced signal processing techniques, in order to discover how the brain is processing auditory targets differently when they possess a rare, salient, unpredictable feature not shared with distractors than when targets lack this feature but distractors have it. We find that brain regions associated with the Ventral Attention Network (VAN) are the primary neural generators of the P3a subcomponent in response to feature-present targets, whereas regions associated with the Dorsal Attention Network (DAN), as well as regions associated with detecting auditory oddball stimuli (ODD), may be the primary neural generators of the P3b, in the context of our study, and perhaps in search paradigms in general. Moreover, measurements of the time courses of oscillatory power changes and inter-regional synchronization in theta and low-gamma frequency bands were consistent with the early activation and synchronization within the VAN associated with the P3a subcomponent, and with the later activation and synchronization within the DAN and ODD networks associated with the P3b subcomponent. Implications of these finding for the mechanisms underlying search asymmetry phenomena are discussed.

Trait Mindfulness and Functional Connectivity in Cognitive and Attentional Resting State Networks.

Mindfulness has been described as an orienting of attention to the present moment, with openness and compassion. Individuals displaying high trait mindfulness exhibit this tendency as a more permanent personality attribute. Given the numerous physical and mental health benefits associated with mindfulness, there is a great interest in understanding the neural substrates of this trait. The purpose of the current research was to examine how individual differences in trait mindfulness associated with functional connectivity in five resting-state networks related to cognition and attention: the default mode network (DMN), the salience network (SN), the central executive network (CEN), and the dorsal and ventral attention networks (DAN and VAN). Twenty-eight undergraduate participants completed the Five-Facet Mindfulness Questionnaire (FFMQ), a self-report measure of trait mindfulness which also provides scores on five of its sub-categories (Observing, Describing, Acting with Awareness, Non-judging of Inner Experience, and Non-reactivity to Inner Experience). Participants then underwent a structural MRI scan and a 7-min resting state functional MRI scan. Resting-state data were analyzed using independent-component analyses. An analysis of covariance (ANCOVA) was performed to determine the relationship between each resting state network and each FFMQ score. These analyses indicated that: (1) trait mindfulness and its facets showed increased functional connectivity with neural regions related to attentional control, interoception, and executive function; and (2) trait mindfulness and its facets showed decreased functional connectivity with neural regions related to self-referential processing and mind wandering. These patterns of functional connectivity are consistent with some of the benefits of mindfulness-enhanced attention, self-regulation, and focus on present experience. This study provides support for the notion that non-judgmental attention to the present moment facilitates the integration of regions in neural networks that are related to cognition, attention, and sensation.

Abdominal multi-organ segmentation with organ-attention networks and statistical fusion.

Accurate and robust segmentation of abdominal organs on CT is essential for many clinical applications such as computer-aided diagnosis and computer-aided surgery. But this task is challenging due to the weak boundaries of organs, the complexity of the background, and the variable sizes of different organs. To address these challenges, we introduce a novel framework for multi-organ segmentation of abdominal regions by using organ-attention networks with reverse connections (OAN-RCs) which are applied to 2D views, of the 3D CT volume, and output estimates which are combined by statistical fusion exploiting structural similarity. More specifically, OAN is a two-stage deep convolutional network, where deep network features from the first stage are combined with the original image, in a second stage, to reduce the complex background and enhance the discriminative information for the target organs. Intuitively, OAN reduces the effect of the complex background by focusing attention so that each organ only needs to be discriminated from its local background. RCs are added to the first stage to give the lower layers more semantic information thereby enabling them to adapt to the sizes of different organs. Our networks are trained on 2D views (slices) enabling us to use holistic information and allowing efficient computation (compared to using 3D patches). To compensate for the limited cross-sectional information of the original 3D volumetric CT, e.g., the connectivity between neighbor slices, multi-sectional images are reconstructed from the three different 2D view directions. Then we combine the segmentation results from the different views using statistical fusion, with a novel term relating the structural similarity of the 2D views to the original 3D structure. To train the network and evaluate results, 13 structures were manually annotated by four human raters and confirmed by a senior expert on 236 normal cases. We tested our algorithm by 4-fold cross-validation and computed Dice-Sørensen similarity coefficients (DSC) and surface distances for evaluating our estimates of the 13 structures. Our experiments show that the proposed approach gives strong results and outperforms 2D- and 3D-patch based state-of-the-art methods in terms of DSC and mean surface distances.

Spiritual experiences are related to engagement of a ventral frontotemporal functional brain network: Implications for prevention and treatment of behavioral and substance addictions.

BACKGROUND AND AIMS: Spirituality is an important component of 12-step programs for behavioral and substance addictions and has been linked to recovery processes. Understanding the neural correlates of spiritual experiences may help to promote efforts to enhance recovery processes in behavioral addictions. We recently used general linear model (GLM) analyses of functional magnetic resonance imaging data to examine neural correlates of spiritual experiences, with findings implicating cortical and subcortical brain regions. Although informative, the GLM-based approach does not provide insight into brain circuits that may underlie spiritual experiences. METHODS: Spatial independent component analysis (sICA) was used to identify functional brain networks specifically linked to spiritual (vs. stressful or neutral-relaxing) conditions using a previously validated guided imagery task in 27 young adults. RESULTS: Using sICA, engagement of a ventral frontotemporal network was identified that was engaged at the onset and conclusion of the spiritual condition in a manner distinct from engagement during the stress or neutral-relaxing conditions. Degree of engagement correlated with subjective reports of spirituality in the scanner (r = .71, p < .001) and an out-of-the-magnet measure of spirituality (r = .48, p < .018). DISCUSSION AND CONCLUSION: The current findings suggest a distributed functional neural network associated with spiritual experiences and provide a foundation for investigating brain mechanisms underlying the role of spirituality in recovery from behavioral addictions.

Enhanced Attentional Network by Short-Term Intensive Meditation.

While recent studies have suggested behavioral effects of short-term meditation on the executive attentional functions, functional changes in the neural correlates of attentional networks after short-term meditation have been unspecified. Here, we conducted a randomized control trial to investigate the effects of a 4-day intensive meditation on the neural correlates of three attentional functions: alerting, orienting, and executive attention. Twenty-three participants in meditation practice and 14 participants in a relaxation retreat group performed attention network test (ANT) during functional magnetic resonance imaging both before and immediately after intervention. The meditation group showed significantly improved behavioral performance in the executive control network in ANT after the intervention. Moreover, neural activities in the executive control network, namely, the anterior cingulate cortex (ACC) and dorsolateral prefrontal cortex (DLPFC), were also significantly increased during the ANT after meditation. Interestingly, neural activity in the right ACC was significantly predicted by behavioral conflict levels in each individual in the meditation group, indicating significant effects of the program on the executive control network. Moreover, brain regions associated with the alerting and orienting networks also showed enhanced activity during the ANT after the meditation. Our study provides novel evidence on the enhancement of the attentional networks at the neural level via short-term meditation. We also suggest that short-term meditation may be beneficial to individuals at high risk of cognitive deficits by improving neural mechanisms of attention.