Multi-Functional 2D Covalent Organic Frameworks with Diketopyrrolopyrrole as Electron Acceptor.

2D covalent organic framework (COF) materials with extended conjugated structure and periodic columnar π-arrays exhibit promising applications in organic optoelectronics. However, there is a scarcity of reports on optoelectronic COFs, mainly due to the lack of suitable π-skeletons. Here, two multi-functional optoelectronic 2D COFs DPP-TPP-COF and DPP-TBB-COF are constructed with diketopyrrolopyrrole as electron acceptor (A), and 1,3,6,8-tetraphenylpyrene and 1,3,5-triphenylbenzene as electron donor (D) through imine bonds. Both 2D COFs showed good crystallinities and AA stacking with a rhombic framework for DPP-TPP-COF and hexagonal one for DPP-TBB-COF, respectively. The electron D-A and ordered intermolecular packing structures endow the COFs with broad UV-vis absorptions and narrow bandgaps along with suitable HOMO/LUMO energy levels, resulting in multi-functional optoelectronic properties, including photothermal conversion, supercapacitor property, and ambipolar semiconducting behavior. Among them, DPP-TPP-COF exhibits a high photothermal conversion efficiency of 47% under 660 nm laser irradiation, while DPP-TBB-COF exhibits superior specific capacitance of 384 F g-1. Moreover, P-type doping and N-type doping are achieved by iodine and tetrakis(dimethylamino)ethylene on a single host COF, resulting in ambipolar semiconducting behavior. These results provide a paradigm for the application of multi-functional optoelectronic COF materials.

Application of propofol-remifentanil intravenous general anesthesia combined with regional block in pediatric ophthalmic surgery.

OBJECTIVE: The aim of this study is to observe the anesthetic effect and safety of intravenous anesthesia without muscle relaxant with propofol-remifentanil combined with regional block under laryngeal mask airway in pediatric ophthalmologic surgery. METHODS: A total of 90 undergoing ophthalmic surgery were anesthetized with general anesthesia using the laryngeal mask airway without muscle relaxant. They were randomly divided into two groups: 45 children who received propofol-remifentanil intravenous anesthesia combined with regional block (LG group), and 45 children who received total intravenous anesthesia (G group). The peri-operative circulatory indicators, awakening time after general anesthesia, postoperative analgesic effect and the incidence of anesthesia-related adverse events were respectively compared between the two groups. RESULTS: All the children successfully underwent the surgical procedure. The awakening time after general anesthesia and removal time of laryngeal mask were significantly shorter in the LG group than in the G group (P < 0.05). There was no statistically significant difference in the heart rates in the perioperative period between the two groups (P > 0.05). There was no statistically significant difference in the incidence of intraoperative physical response, respiratory depression, postoperative nausea and vomiting (PONV) and emergence agitation (EA) between the two groups (P > 0.05). The pain score at the postoperative hour 2 was lower in the LG group than in the G group (P < 0.05). CONCLUSION: Propofol-remifentanil intravenous anesthesia combined with long-acting local anesthetic regional block anesthesia, combined with laryngeal mask ventilation technology without muscle relaxants, can be safely used in pediatric eye surgery to achieve rapid and smooth recovery from general anesthesia and better postoperative analgesia. This anesthesia scheme can improve the comfort and safety of children in perioperative period, and has a certain clinical popularization value.

Hybridizing aggregated gold nanoparticles with a hydrogel to prepare a flexible SERS chip for detecting organophosphorus pesticides.

Surface enhanced Raman scattering (SERS) is an ultrasensitive analytic technique. However, the application of SERS in quantitative analysis usually suffers from poor reliability due to the limitations of currently developed SERS substrates. In the present work, aggregated gold nanoparticles (a-AuNPs) fabricated by Ca2+-mediated assembly are dispersed in polyvinyl alcohol solution to prepare a novel hydrogel SERS chip through a physical crosslinking method. Taking advantage of the uniform distribution of SERS active a-AuNPs in the three-dimension hydrogel and the excellent barrier effect of hydrogel towards oxygen and macromolecules, the obtained hydrogel SERS chips show many outstanding advantages including high sensitivity, good repeatability, long-term stability, and a robust anti-interference ability. These advantages enable hydrogel SERS chips to be used to quantitatively analyse some complex samples without complex sample preprocessing. As a model, the hydrogel SERS chips are used for the detection of triazophos and phosmet in orange samples. The good recoveries suggest good applicability of the hydrogel SERS chips in food safety detection. This work provides a reliable and convenient platform for the quick detection and on-site monitoring of chemical contaminants and would promote greatly the performance of SERS techniques in quantitative analysis.

Induced effect of Ca2+ and Al3+ on chaetominine synthesis by Aspergillus fumigatus CY018 under submerged fermentation.

Chaetominine (CHA), an alkaloid with a biological activity obtained from Aspergillus fumigatus CY018, has strong anticancer activity against the human leukemia cells. However, its physiological and biochemical research is limited by CHA yield in the liquid-state fermentation, which is a problem that urgently needs effective biological solution. In this work, Ca2+ and Al3+ were found to have a strong promoting effect on CHA production after multiple metal ions screening. Then, the addition condition of Ca2+ and Al3+ was, respectively, optimized CHA production and dry cell weight. The intermediate metabolites were increased with coaddition of Ca2+ and Al3+ . The activities of key enzymes of DAHPs, AroAs, and TrpCs in the CHA biosynthesis pathway were improved by 3.58-, 3.60-, and 3.34-fold, respectively. Meanwhile, the transcription level of laeA, dahp, cs, and trpC was upregulated by 3.22-, 12.65-, 5.58-, and 6.99-fold, respectively, by coaddition of Ca2+ and Al3+ . Additionally, the fermentation strategy was successfully scaled up to a 5-L bioreactor, in which CHA production could attain 75.6 mg/L at 336 h. This work demonstrated that Ca2+ and Al3+ coaddition was an effective strategy for increasing CHA production, and the information obtained might be useful in the fermentation of filamentous fungi with the addition of metal ions.

Direct Delivery of Antisense Oligonucleotides to the Middle and Inner Ear Improves Hearing and Balance in Usher Mice.

Usher syndrome is a syndromic form of hereditary hearing impairment that includes sensorineural hearing loss and delayed-onset retinitis pigmentosa (RP). Type 1 Usher syndrome (USH1) is characterized by congenital profound sensorineural hearing impairment and vestibular areflexia, with adolescent-onset RP. Systemic treatment with antisense oligonucleotides (ASOs) targeting the human USH1C c.216G>A splicing mutation in a knockin mouse model of USH1 restores hearing and balance. Herein, we explore the effect of delivering ASOs locally to the ear to treat hearing and vestibular dysfunction associated with Usher syndrome. Three localized delivery strategies were investigated in USH1C mice: inner ear injection, trans-tympanic membrane injection, and topical tympanic membrane application. We demonstrate, for the first time, that ASOs delivered directly to the ear correct Ush1c expression in inner ear tissue, improve cochlear hair cell transduction currents, restore vestibular afferent irregularity, spontaneous firing rate, and sensitivity to head rotation, and successfully recover hearing thresholds and balance behaviors in USH1C mice. We conclude that local delivery of ASOs to the middle and inner ear reach hair cells and can rescue both hearing and balance. These results also demonstrate the therapeutic potential of ASOs to treat hearing and balance deficits associated with Usher syndrome and other ear diseases.

Distinct Global Brain Dynamics and Spatiotemporal Organization of the Salience Network.

One of the most fundamental features of the human brain is its ability to detect and attend to salient goal-relevant events in a flexible manner. The salience network (SN), anchored in the anterior insula and the dorsal anterior cingulate cortex, plays a crucial role in this process through rapid detection of goal-relevant events and facilitation of access to appropriate cognitive resources. Here, we leverage the subsecond resolution of large multisession fMRI datasets from the Human Connectome Project and apply novel graph-theoretical techniques to investigate the dynamic spatiotemporal organization of the SN. We show that the large-scale brain dynamics of the SN are characterized by several distinctive and robust properties. First, the SN demonstrated the highest levels of flexibility in time-varying connectivity with other brain networks, including the frontoparietal network (FPN), the cingulate-opercular network (CON), and the ventral and dorsal attention networks (VAN and DAN). Second, dynamic functional interactions of the SN were among the most spatially varied in the brain. Third, SN nodes maintained a consistently high level of network centrality over time, indicating that this network is a hub for facilitating flexible cross-network interactions. Fourth, time-varying connectivity profiles of the SN were distinct from all other prefrontal control systems. Fifth, temporal flexibility of the SN uniquely predicted individual differences in cognitive flexibility. Importantly, each of these results was also observed in a second retest dataset, demonstrating the robustness of our findings. Our study provides fundamental new insights into the distinct dynamic functional architecture of the SN and demonstrates how this network is uniquely positioned to facilitate interactions with multiple functional systems and thereby support a wide range of cognitive processes in the human brain.

Neural circuits underlying mother's voice perception predict social communication abilities in children.

The human voice is a critical social cue, and listeners are extremely sensitive to the voices in their environment. One of the most salient voices in a child's life is mother's voice: Infants discriminate their mother's voice from the first days of life, and this stimulus is associated with guiding emotional and social function during development. Little is known regarding the functional circuits that are selectively engaged in children by biologically salient voices such as mother's voice or whether this brain activity is related to children's social communication abilities. We used functional MRI to measure brain activity in 24 healthy children (mean age, 10.2 y) while they attended to brief (<1 s) nonsense words produced by their biological mother and two female control voices and explored relationships between speech-evoked neural activity and social function. Compared to female control voices, mother's voice elicited greater activity in primary auditory regions in the midbrain and cortex; voice-selective superior temporal sulcus (STS); the amygdala, which is crucial for processing of affect; nucleus accumbens and orbitofrontal cortex of the reward circuit; anterior insula and cingulate of the salience network; and a subregion of fusiform gyrus associated with face perception. The strength of brain connectivity between voice-selective STS and reward, affective, salience, memory, and face-processing regions during mother's voice perception predicted social communication skills. Our findings provide a novel neurobiological template for investigation of typical social development as well as clinical disorders, such as autism, in which perception of biologically and socially salient voices may be impaired.

Positive Attitude Toward Math Supports Early Academic Success: Behavioral Evidence and Neurocognitive Mechanisms.

Positive attitude is thought to impact academic achievement and learning in children, but little is known about its underlying neurocognitive mechanisms. Using a large behavioral sample of 240 children, we found that positive attitude toward math uniquely predicted math achievement, even after we accounted for multiple other cognitive-affective factors. We then investigated the neural mechanisms underlying the link between positive attitude and academic achievement in two independent cohorts of children (discovery cohort: n = 47; replication cohort: n = 28) and tested competing hypotheses regarding the differential roles of affective-motivational and learning-memory systems. In both cohorts, we found that positive attitude was associated with increased engagement of the hippocampal learning-memory system. Structural equation modeling further revealed that, in both cohorts, increased hippocampal activity and more frequent use of efficient memory-based strategies mediated the relation between positive attitude and higher math achievement. Our study is the first to elucidate the neurocognitive mechanisms by which positive attitude influences learning and academic achievement.

Dissociable Fronto-Operculum-Insula Control Signals for Anticipation and Detection of Inhibitory Sensory Cue.

The ability to anticipate and detect behaviorally salient stimuli is important for virtually all adaptive behaviors, including inhibitory control that requires the withholding of prepotent responses when instructed by external cues. Although right fronto-operculum-insula (FOI), encompassing the anterior insular cortex (rAI) and inferior frontal cortex (rIFC), involvement in inhibitory control is well established, little is known about signaling mechanisms underlying their differential roles in detection and anticipation of salient inhibitory cues. Here we use 2 independent functional magnetic resonance imaging data sets to investigate dynamic causal interactions of the rAI and rIFC, with sensory cortex during detection and anticipation of inhibitory cues. Across 2 different experiments involving auditory and visual inhibitory cues, we demonstrate that primary sensory cortex has a stronger causal influence on rAI than on rIFC, suggesting a greater role for the rAI in detection of salient inhibitory cues. Crucially, a Bayesian prediction model of subjective trial-by-trial changes in inhibitory cue anticipation revealed that the strength of causal influences from rIFC to rAI increased significantly on trials in which participants had higher anticipation of inhibitory cues. Together, these results demonstrate the dissociable bottom-up and top-down roles of distinct FOI regions in detection and anticipation of behaviorally salient cues across multiple sensory modalities.

Bayesian switching factor analysis for estimating time-varying functional connectivity in fMRI.

There is growing interest in understanding the dynamical properties of functional interactions between distributed brain regions. However, robust estimation of temporal dynamics from functional magnetic resonance imaging (fMRI) data remains challenging due to limitations in extant multivariate methods for modeling time-varying functional interactions between multiple brain areas. Here, we develop a Bayesian generative model for fMRI time-series within the framework of hidden Markov models (HMMs). The model is a dynamic variant of the static factor analysis model (Ghahramani and Beal, 2000). We refer to this model as Bayesian switching factor analysis (BSFA) as it integrates factor analysis into a generative HMM in a unified Bayesian framework. In BSFA, brain dynamic functional networks are represented by latent states which are learnt from the data. Crucially, BSFA is a generative model which estimates the temporal evolution of brain states and transition probabilities between states as a function of time. An attractive feature of BSFA is the automatic determination of the number of latent states via Bayesian model selection arising from penalization of excessively complex models. Key features of BSFA are validated using extensive simulations on carefully designed synthetic data. We further validate BSFA using fingerprint analysis of multisession resting-state fMRI data from the Human Connectome Project (HCP). Our results show that modeling temporal dependencies in the generative model of BSFA results in improved fingerprinting of individual participants. Finally, we apply BSFA to elucidate the dynamic functional organization of the salience, central-executive, and default mode networks-three core neurocognitive systems with central role in cognitive and affective information processing (Menon, 2011). Across two HCP sessions, we demonstrate a high level of dynamic interactions between these networks and determine that the salience network has the highest temporal flexibility among the three networks. Our proposed methods provide a novel and powerful generative model for investigating dynamic brain connectivity.

Temporal Dynamics and Developmental Maturation of Salience, Default and Central-Executive Network Interactions Revealed by Variational Bayes Hidden Markov Modeling.

Little is currently known about dynamic brain networks involved in high-level cognition and their ontological basis. Here we develop a novel Variational Bayesian Hidden Markov Model (VB-HMM) to investigate dynamic temporal properties of interactions between salience (SN), default mode (DMN), and central executive (CEN) networks-three brain systems that play a critical role in human cognition. In contrast to conventional models, VB-HMM revealed multiple short-lived states characterized by rapid switching and transient connectivity between SN, CEN, and DMN. Furthermore, the three "static" networks occurred in a segregated state only intermittently. Findings were replicated in two adult cohorts from the Human Connectome Project. VB-HMM further revealed immature dynamic interactions between SN, CEN, and DMN in children, characterized by higher mean lifetimes in individual states, reduced switching probability between states and less differentiated connectivity across states. Our computational techniques provide new insights into human brain network dynamics and its maturation with development.

Causal Interactions Within a Frontal-Cingulate-Parietal Network During Cognitive Control: Convergent Evidence from a Multisite-Multitask Investigation.

Cognitive control plays an important role in goal-directed behavior, but dynamic brain mechanisms underlying it are poorly understood. Here, using multisite fMRI data from over 100 participants, we investigate causal interactions in three cognitive control tasks within a core Frontal-Cingulate-Parietal network. We found significant causal influences from anterior insula (AI) to dorsal anterior cingulate cortex (dACC) in all three tasks. The AI exhibited greater net causal outflow than any other node in the network. Importantly, a similar pattern of causal interactions was uncovered by two different computational methods for causal analysis. Furthermore, the strength of causal interaction from AI to dACC was greater on high, compared with low, cognitive control trials and was significantly correlated with individual differences in cognitive control abilities. These results emphasize the importance of the AI in cognitive control and highlight its role as a causal hub in the Frontal-Cingulate-Parietal network. Our results further suggest that causal signaling between the AI and dACC plays a fundamental role in implementing cognitive control and are consistent with a two-stage cognitive control model in which the AI first detects events requiring greater access to cognitive control resources and then signals the dACC to execute load-specific cognitive control processes.

Diagnostic accuracy of ultrasonographic features for lymph node metastasis in papillary thyroid microcarcinoma: a single-center retrospective study.

BACKGROUND: Whether sonography is an appropriate imaging modality for cervical lymph nodes in patients with papillary thyroid microcarcinoma (PTMC) remains unclear. Hence, this study aimed to evaluate the diagnostic value of ultrasonography (US) features for lymph node metastasis in PTMC. METHODS: Seven hundred twelve patients with PTMC who underwent conventional ultrasonography examinations of the cervical lymph nodes were included. All included cases underwent total thyroidectomy plus prophylactic central lymph node dissection. The included lymph nodes were marked superficially, and the corresponding lymph nodes were completely removed and sent for pathological examination. The US features of lymph nodes with and without metastasis were compared, and the odds ratios of the suspicious US features were determined with univariate and multivariate analyses. RESULTS: Round shape, loss of an echogenic fatty hilum, cystic change, calcification, and abnormal vascularity were significantly more common in metastatic than nonmetastatic lymph nodes, whereas the boundary and echo did not significantly differ. Multivariate logistic regression analysis showed that round shape, loss of echogenic fatty hilum, cystic change, calcification, and abnormal vascularity were independent predictive factors for the assessment of metastatic lymph nodes. Round shape had the highest sensitivity of all variables, while loss of an echogenic fatty hilum had the highest specificity and accuracy. The area under the receiver operating characteristic curve, which was calculated to verify the relationship between the various US features and metastatic lymph nodes, was 0.793. CONCLUSIONS: Our study found that the US features of round shape, cystic change, calcification, loss of echogenic fatty hilum, and abnormal vascularity were useful sonographic criteria for differentiating between cervical lymph nodes with and without metastasis.

Heterogeneous and nonlinear development of human posterior parietal cortex function.

Human cognitive problem solving skills undergo complex experience-dependent changes from childhood to adulthood, yet most neurodevelopmental research has focused on linear changes with age. Here we challenge this limited view, and investigate spatially heterogeneous and nonlinear neurodevelopmental profiles between childhood, adolescence, and young adulthood, focusing on three cytoarchitectonically distinct posterior parietal cortex (PPC) regions implicated in numerical problem solving: intraparietal sulcus (IPS), angular gyrus (AG), and supramarginal gyrus (SMG). Adolescents demonstrated better behavioral performance relative to children, but their performance was equivalent to that of adults. However, all three groups differed significantly in their profile of activation and connectivity across the PPC subdivisions. Activation in bilateral ventral IPS subdivision IPS-hIP1, along with adjoining anterior AG subdivision, AG-PGa, and the posterior SMG subdivision, SMG-PFm, increased linearly with age, whereas the posterior AG subdivision, AG-PGp, was equally deactivated in all three groups. In contrast, the left anterior SMG subdivision, SMG-PF, showed an inverted U-shaped profile across age groups such that adolescents exhibited greater activation than both children and young adults. Critically, greater SMG-PF activation was correlated with task performance only in adolescents. Furthermore, adolescents showed greater task-related functional connectivity of the SMG-PF with ventro-temporal, anterior temporal and prefrontal cortices, relative to both children and adults. These results suggest that nonlinear up-regulation of SMG-PF and its interconnected functional circuits facilitate adult-level performance in adolescents. Our study provides novel insights into heterogeneous age-related maturation of the PPC underlying cognitive skill acquisition, and further demonstrates how anatomically precise analysis of both linear and nonlinear neurofunctional changes with age is necessary for more fully characterizing cognitive development.

Combining optogenetic stimulation and fMRI to validate a multivariate dynamical systems model for estimating causal brain interactions.

State-space multivariate dynamical systems (MDS) (Ryali et al. 2011) and other causal estimation models are being increasingly used to identify directed functional interactions between brain regions. However, the validity and accuracy of such methods are poorly understood. Performance evaluation based on computer simulations of small artificial causal networks can address this problem to some extent, but they often involve simplifying assumptions that reduce biological validity of the resulting data. Here, we use a novel approach taking advantage of recently developed optogenetic fMRI (ofMRI) techniques to selectively stimulate brain regions while simultaneously recording high-resolution whole-brain fMRI data. ofMRI allows for a more direct investigation of causal influences from the stimulated site to brain regions activated downstream and is therefore ideal for evaluating causal estimation methods in vivo. We used ofMRI to investigate whether MDS models for fMRI can accurately estimate causal functional interactions between brain regions. Two cohorts of ofMRI data were acquired, one at Stanford University and the University of California Los Angeles (Cohort 1) and the other at the University of North Carolina Chapel Hill (Cohort 2). In each cohort, optical stimulation was delivered to the right primary motor cortex (M1). General linear model analysis revealed prominent downstream thalamic activation in Cohort 1, and caudate-putamen (CPu) activation in Cohort 2. MDS accurately estimated causal interactions from M1 to thalamus and from M1 to CPu in Cohort 1 and Cohort 2, respectively. As predicted, no causal influences were found in the reverse direction. Additional control analyses demonstrated the specificity of causal interactions between stimulated and target sites. Our findings suggest that MDS state-space models can accurately and reliably estimate causal interactions in ofMRI data and further validate their use for estimating causal interactions in fMRI. More generally, our study demonstrates that the combined use of optogenetics and fMRI provides a powerful new tool for evaluating computational methods designed to estimate causal interactions between distributed brain regions.

Parietal hyper-connectivity, aberrant brain organization, and circuit-based biomarkers in children with mathematical disabilities.

Mathematical disabilities (MD) have a negative life-long impact on professional success, employment, and health outcomes. Yet little is known about the intrinsic functional brain organization that contributes to poor math skills in affected children. It is now increasingly recognized that math cognition requires coordinated interaction within a large-scale fronto-parietal network anchored in the intraparietal sulcus (IPS). Here we characterize intrinsic functional connectivity within this IPS-network in children with MD, relative to a group of typically developing (TD) children who were matched on age, gender, IQ, working memory, and reading abilities. Compared to TD children, children with MD showed hyper-connectivity of the IPS with a bilateral fronto-parietal network. Importantly, aberrant IPS connectivity patterns accurately discriminated children with MD and TD children, highlighting the possibility for using IPS connectivity as a brain-based biomarker of MD. To further investigate regional abnormalities contributing to network-level deficits in children with MD, we performed whole-brain analyses of intrinsic low-frequency fluctuations. Notably, children with MD showed higher low-frequency fluctuations in multiple fronto-parietal areas that overlapped with brain regions that exhibited hyper-connectivity with the IPS. Taken together, our findings suggest that MD in children is characterized by robust network-level aberrations, and is not an isolated dysfunction of the IPS. We hypothesize that intrinsic hyper-connectivity and enhanced low-frequency fluctuations may limit flexible resource allocation, and contribute to aberrant recruitment of task-related brain regions during numerical problem solving in children with MD.

Associations between BRAF(V600E) and prognostic factors and poor outcomes in papillary thyroid carcinoma: a meta-analysis.

BACKGROUND: The objective of this study is to perform a meta-analysis to evaluate the associations between the BRAF(V600E) mutation status and aggressive clinicopathological features and poor prognostic factors in papillary thyroid cancer. METHODS: A literature search was performed within the PubMed, MEDLINE, Web of Science databases, and EMBASE databases using the Medical Subject Headings and keywords from January 2003 to July 2015. Individual study-specific odds ratios and confidence intervals were calculated, as were the Mantel-Haenszel pooled odds ratios for the combined studies. RESULTS: Sixty-three studies of 20,764 patients were included in the final analysis. Compared with wild-type BRAF, the BRAF(V600E) mutation was associated with aggressive clinicopathological factors, including extrathyroidal extension, higher TNM stage, lymph node metastasis, and recurrence, and was associated with reduced overall survival; however, there was no significant association between the presence of BRAF mutation and distant metastasis. CONCLUSIONS: BRAF mutations are closely associated with aggressive clinicopathological characteristics and poorer prognosis in papillary thyroid cancer. Accordingly, aggressive treatment should be considered for papillary thyroid cancer patients with BRAF mutation.

Dissociable roles of right inferior frontal cortex and anterior insula in inhibitory control: evidence from intrinsic and task-related functional parcellation, connectivity, and response profile analyses across multiple datasets.

The right inferior frontal cortex (rIFC) and the right anterior insula (rAI) have been implicated consistently in inhibitory control, but their differential roles are poorly understood. Here we use multiple quantitative techniques to dissociate the functional organization and roles of the rAI and rIFC. We first conducted a meta-analysis of 70 published inhibitory control studies to generate a commonly activated right fronto-opercular cortex volume of interest (VOI). We then segmented this VOI using two types of features: (1) intrinsic brain activity; and (2) stop-signal task-evoked hemodynamic response profiles. In both cases, segmentation algorithms identified two stable and distinct clusters encompassing the rAI and rIFC. The rAI and rIFC clusters exhibited several distinct functional characteristics. First, the rAI showed stronger intrinsic and task-evoked functional connectivity with the anterior cingulate cortex, whereas the rIFC had stronger intrinsic and task-evoked functional connectivity with dorsomedial prefrontal and lateral fronto-parietal cortices. Second, the rAI showed greater activation than the rIFC during Unsuccessful, but not Successful, Stop trials, and multivoxel response profiles in the rAI, but not the rIFC, accurately differentiated between Successful and Unsuccessful Stop trials. Third, activation in the rIFC, but not rAI, predicted individual differences in inhibitory control abilities. Crucially, these findings were replicated in two independent cohorts of human participants. Together, our findings provide novel quantitative evidence for the dissociable roles of the rAI and rIFC in inhibitory control. We suggest that the rAI is particularly important for detecting behaviorally salient events, whereas the rIFC is more involved in implementing inhibitory control.

Role of the anterior insular cortex in integrative causal signaling during multisensory auditory-visual attention.

Coordinated attention to information from multiple senses is fundamental to our ability to respond to salient environmental events, yet little is known about brain network mechanisms that guide integration of information from multiple senses. Here we investigate dynamic causal mechanisms underlying multisensory auditory-visual attention, focusing on a network of right-hemisphere frontal-cingulate-parietal regions implicated in a wide range of tasks involving attention and cognitive control. Participants performed three 'oddball' attention tasks involving auditory, visual and multisensory auditory-visual stimuli during fMRI scanning. We found that the right anterior insula (rAI) demonstrated the most significant causal influences on all other frontal-cingulate-parietal regions, serving as a major causal control hub during multisensory attention. Crucially, we then tested two competing models of the role of the rAI in multisensory attention: an 'integrated' signaling model in which the rAI generates a common multisensory control signal associated with simultaneous attention to auditory and visual oddball stimuli versus a 'segregated' signaling model in which the rAI generates two segregated and independent signals in each sensory modality. We found strong support for the integrated, rather than the segregated, signaling model. Furthermore, the strength of the integrated control signal from the rAI was most pronounced on the dorsal anterior cingulate and posterior parietal cortices, two key nodes of saliency and central executive networks respectively. These results were preserved with the addition of a superior temporal sulcus region involved in multisensory processing. Our study provides new insights into the dynamic causal mechanisms by which the AI facilitates multisensory attention.

Brain hyper-connectivity and operation-specific deficits during arithmetic problem solving in children with developmental dyscalculia.

Developmental dyscalculia (DD) is marked by specific deficits in processing numerical and mathematical information despite normal intelligence (IQ) and reading ability. We examined how brain circuits used by young children with DD to solve simple addition and subtraction problems differ from those used by typically developing (TD) children who were matched on age, IQ, reading ability, and working memory. Children with DD were slower and less accurate during problem solving than TD children, and were especially impaired on their ability to solve subtraction problems. Children with DD showed significantly greater activity in multiple parietal, occipito-temporal and prefrontal cortex regions while solving addition and subtraction problems. Despite poorer performance during subtraction, children with DD showed greater activity in multiple intra-parietal sulcus (IPS) and superior parietal lobule subdivisions in the dorsal posterior parietal cortex as well as fusiform gyrus in the ventral occipito-temporal cortex. Critically, effective connectivity analyses revealed hyper-connectivity, rather than reduced connectivity, between the IPS and multiple brain systems including the lateral fronto-parietal and default mode networks in children with DD during both addition and subtraction. These findings suggest the IPS and its functional circuits are a major locus of dysfunction during both addition and subtraction problem solving in DD, and that inappropriate task modulation and hyper-connectivity, rather than under-engagement and under-connectivity, are the neural mechanisms underlying problem solving difficulties in children with DD. We discuss our findings in the broader context of multiple levels of analysis and performance issues inherent in neuroimaging studies of typical and atypical development.