Population heterogeneity in clinical cohorts affects the predictive accuracy of brain imaging.

Brain imaging research enjoys increasing adoption of supervised machine learning for single-participant disease classification. Yet, the success of these algorithms likely depends on population diversity, including demographic differences and other factors that may be outside of primary scientific interest. Here, we capitalize on propensity scores as a composite confound index to quantify diversity due to major sources of population variation. We delineate the impact of population heterogeneity on the predictive accuracy and pattern stability in 2 separate clinical cohorts: the Autism Brain Imaging Data Exchange (ABIDE, n = 297) and the Healthy Brain Network (HBN, n = 551). Across various analysis scenarios, our results uncover the extent to which cross-validated prediction performances are interlocked with diversity. The instability of extracted brain patterns attributable to diversity is located preferentially in regions part of the default mode network. Collectively, our findings highlight the limitations of prevailing deconfounding practices in mitigating the full consequences of population diversity.

Connectome reorganization associated with temporal lobe pathology and its surgical resection.

Network neuroscience offers a unique framework to understand the organizational principles of the human brain. Despite recent progress, our understanding of how the brain is modulated by focal lesions remains incomplete. Resection of the temporal lobe is the most effective treatment to control seizures in pharmaco-resistant temporal lobe epilepsy (TLE), making this syndrome a powerful model to study lesional effects on network organization in young and middle-aged adults. Here, we assessed the downstream consequences of a focal lesion and its surgical resection on the brain's structural connectome, and explored how this reorganization relates to clinical variables at the individual patient level. We included adults with pharmaco-resistant TLE (n = 37) who underwent anterior temporal lobectomy between two imaging time points, as well as age- and sex-matched healthy controls who underwent comparable imaging (n = 31). Core to our analysis was the projection of high-dimensional structural connectome data-derived from diffusion MRI tractography from each subject-into lower-dimensional gradients. We then compared connectome gradients in patients relative to controls before surgery, tracked surgically-induced connectome reconfiguration from pre- to postoperative time points, and examined associations to patient-specific clinical and imaging phenotypes. Before surgery, individuals with TLE presented with marked connectome changes in bilateral temporo-parietal regions, reflecting an increased segregation of the ipsilateral anterior temporal lobe from the rest of the brain. Surgery-induced connectome reorganization was localized to this temporo-parietal subnetwork, but primarily involved postoperative integration of contralateral regions with the rest of the brain. Using a partial least-squares analysis, we uncovered a latent clinical imaging signature underlying this pre- to postoperative connectome reorganization, showing that patients who displayed postoperative integration in bilateral fronto-occipital cortices also had greater preoperative ipsilateral hippocampal atrophy, lower seizure frequency and secondarily generalized seizures. Our results bridge the effects of focal brain lesions and their surgical resections with large-scale network reorganization and interindividual clinical variability, thus offering new avenues to examine the fundamental malleability of the human brain.

Adolescent development of multiscale structural wiring and functional interactions in the human connectome.

Adolescence is a time of profound changes in the physical wiring and function of the brain. Here, we analyzed structural and functional brain network development in an accelerated longitudinal cohort spanning 14 to 25 y (n = 199). Core to our work was an advanced in vivo model of cortical wiring incorporating MRI features of corticocortical proximity, microstructural similarity, and white matter tractography. Longitudinal analyses assessing age-related changes in cortical wiring identified a continued differentiation of multiple corticocortical structural networks in youth. We then assessed structure-function coupling using resting-state functional MRI measures in the same participants both via cross-sectional analysis at baseline and by studying longitudinal change between baseline and follow-up scans. At baseline, regions with more similar structural wiring were more likely to be functionally coupled. Moreover, correlating longitudinal structural wiring changes with longitudinal functional connectivity reconfigurations, we found that increased structural differentiation, particularly between sensory/unimodal and default mode networks, was reflected by reduced functional interactions. These findings provide insights into adolescent development of human brain structure and function, illustrating how structural wiring interacts with the maturation of macroscale functional hierarchies.

Diffusion time-related structure-function coupling reveals differential association with inter-individual variations in body mass index.

Body mass index (BMI) is an indicator of obesity, and recent neuroimaging studies have demonstrated that inter-individual variations in BMI are associated with altered brain structure and function. However, the mechanism underlying the alteration of structure-function correspondence according to BMI is under-investigated. In this study, we studied structural and functional connectivity derived from diffusion MRI tractography and inter-regional correlations of functional MRI time series, respectively. We combined the structural and functional connectivity information using the Riemannian optimization approach. First, the low-dimensional principal eigenvectors (i.e., gradients) of the structural connectivity were generated by applying diffusion map embedding with varying diffusion times. A transformation was identified so that the structural and functional embeddings share the same coordinate system, and subsequently, the functional connectivity matrix was simulated. Then, we generated gradients from the simulated functional connectivity matrix. We found the most apparent cortical hierarchical organization differentiating between low-level sensory and higher-order transmodal regions in the middle of the diffusion time, indicating that the hierarchical organization of the brain may reflect the intermediate mechanisms of mono- and polysynaptic communications. Associations between the functional gradients and BMI were strongest when the hierarchical structure was the most evident. Moreover, the gradient-BMI association map was related to the microstructural features, and the findings indicated that the BMI-related structure-function coupling was significantly associated with brain microstructure, particularly in higher-order transmodal areas. Finally, transcriptomic association analysis revealed the potential biological underpinnings specifying gene enrichment in the striatum, hypothalamus, and cortical cells. Our findings provide evidence that structure-function correspondence is strongly coupled with BMI when hierarchical organization is the most apparent and that the associations are related to the multiscale properties of the brain, leading to an advanced understanding of the neural mechanisms related to BMI.

Whole-brain structural connectome asymmetry in autism.

Autism spectrum disorder is a common neurodevelopmental condition that manifests as a disruption in sensory and social skills. Although it has been shown that the brain morphology of individuals with autism is asymmetric, how this differentially affects the structural connectome organization of each hemisphere remains under-investigated. We studied whole-brain structural connectivity-based brain asymmetry in individuals with autism using diffusion magnetic resonance imaging obtained from the Autism Brain Imaging Data Exchange initiative. By leveraging dimensionality reduction techniques, we constructed low-dimensional representations of structural connectivity and calculated their asymmetry index. Comparing the asymmetry index between individuals with autism and neurotypical controls, we found atypical structural connectome asymmetry in the sensory and default-mode regions, particularly showing weaker asymmetry towards the right hemisphere in autism. Network communication provided topological underpinnings by demonstrating that the inferior temporal cortex and limbic and frontoparietal regions showed reduced global network communication efficiency and decreased send-receive network navigation in the inferior temporal and lateral visual cortices in individuals with autism. Finally, supervised machine learning revealed that structural connectome asymmetry could be used as a measure for predicting communication-related autistic symptoms and nonverbal intelligence. Our findings provide insights into macroscale structural connectome alterations in autism and their topological underpinnings.

Connectome-wide structure-function coupling models implicate polysynaptic alterations in autism.

Autism spectrum disorder (ASD) is one of the most common neurodevelopmental diagnoses. Although incompletely understood, structural and functional network alterations are increasingly recognized to be at the core of the condition. We utilized multimodal imaging and connectivity modeling to study structure-function coupling in ASD and probed mono- and polysynaptic mechanisms on structurally-governed network function. We examined multimodal magnetic resonance imaging data in 80 ASD and 61 neurotypical controls from the Autism Brain Imaging Data Exchange (ABIDE) II initiative. We predicted intrinsic functional connectivity from structural connectivity data in each participant using a Riemannian optimization procedure that varies the times that simulated signals can unfold along tractography-derived personalized connectomes. In both ASD and neurotypical controls, we observed improved structure-function prediction at longer diffusion time scales, indicating better modeling of brain function when polysynaptic mechanisms are accounted for. Prediction accuracy differences (∆prediction accuracy) were marked in transmodal association systems, such as the default mode network, in both neurotypical controls and ASD. Differences were, however, lower in ASD in a polysynaptic regime at higher simulated diffusion times. We compared regional differences in ∆prediction accuracy between both groups to assess the impact of polysynaptic communication on structure-function coupling. This analysis revealed that between-group differences in ∆prediction accuracy followed a sensory-to-transmodal cortical hierarchy, with an increased gap between controls and ASD in transmodal compared to sensory/motor systems. Multivariate associative techniques revealed that structure-function differences reflected inter-individual differences in autistic symptoms and verbal as well as non-verbal intelligence. Our network modeling approach sheds light on atypical structure-function coupling in autism, and suggests that polysynaptic network mechanisms are implicated in the condition and that these can help explain its wide range of associated symptoms.

GAN-MAT: Generative adversarial network-based microstructural profile covariance analysis toolbox.

Multimodal magnetic resonance imaging (MRI) provides complementary information for investigating brain structure and function; for example, an in vivo microstructure-sensitive proxy can be estimated using the ratio between T1- and T2-weighted structural MRI. However, acquiring multiple imaging modalities is challenging in patients with inattentive disorders. In this study, we proposed a comprehensive framework to provide multiple imaging features related to the brain microstructure using only T1-weighted MRI. Our toolbox consists of (i) synthesizing T2-weighted MRI from T1-weighted MRI using a conditional generative adversarial network; (ii) estimating microstructural features, including intracortical covariance and moment features of cortical layer-wise microstructural profiles; and (iii) generating a microstructural gradient, which is a low-dimensional representation of the intracortical microstructure profile. We trained and tested our toolbox using T1- and T2-weighted MRI scans of 1,104 healthy young adults obtained from the Human Connectome Project database. We found that the synthesized T2-weighted MRI was very similar to the actual image and that the synthesized data successfully reproduced the microstructural features. The toolbox was validated using an independent dataset containing healthy controls and patients with episodic migraine as well as the atypical developmental condition of autism spectrum disorder. Our toolbox may provide a new paradigm for analyzing multimodal structural MRI in the neuroscience community and is openly accessible at https://github.com/CAMIN-neuro/GAN-MAT.

Identifying subgroups of eating behavior traits unrelated to obesity using functional connectivity and feature representation learning.

Eating behavior is highly heterogeneous across individuals and cannot be fully explained using only the degree of obesity. We utilized unsupervised machine learning and functional connectivity measures to explore the heterogeneity of eating behaviors measured by a self-assessment instrument using 424 healthy adults (mean ± standard deviation [SD] age = 47.07 ± 18.89 years; 67% female). We generated low-dimensional representations of functional connectivity using resting-state functional magnetic resonance imaging and estimated latent features using the feature representation capabilities of an autoencoder by nonlinearly compressing the functional connectivity information. The clustering approaches applied to latent features identified three distinct subgroups. The subgroups exhibited different levels of hunger traits, while their body mass indices were comparable. The results were replicated in an independent dataset consisting of 212 participants (mean ± SD age = 38.97 ± 19.80 years; 35% female). The model interpretation technique of integrated gradients revealed that the between-group differences in the integrated gradient maps were associated with functional reorganization in heteromodal association and limbic cortices and reward-related subcortical structures such as the accumbens, amygdala, and caudate. The cognitive decoding analysis revealed that these systems are associated with reward- and emotion-related systems. Our findings provide insights into the macroscopic brain organization of eating behavior-related subgroups independent of obesity.

Structural connectome alterations between individuals with autism and neurotypical controls using feature representation learning.

Autism spectrum disorder is one of the most common neurodevelopmental conditions associated with sensory and social communication impairments. Previous neuroimaging studies reported that atypical nodal- or network-level functional brain organization in individuals with autism was associated with autistic behaviors. Although dimensionality reduction techniques have the potential to uncover new biomarkers, the analysis of whole-brain structural connectome abnormalities in a low-dimensional latent space is underinvestigated. In this study, we utilized autoencoder-based feature representation learning for diffusion magnetic resonance imaging-based structural connectivity in 80 individuals with autism and 61 neurotypical controls that passed strict quality controls. We generated low-dimensional latent features using the autoencoder model for each group and adopted an integrated gradient approach to assess the contribution of the input data for predicting latent features during the encoding process. Subsequently, we compared the integrated gradient values between individuals with autism and neurotypical controls and observed differences within the transmodal regions and between the sensory and limbic systems. Finally, we identified significant associations between integrated gradient values and communication abilities in individuals with autism. Our findings provide insights into the whole-brain structural connectome in autism and may help identify potential biomarkers for autistic connectopathy.

Cortical microstructural gradients capture memory network reorganization in temporal lobe epilepsy.

Temporal lobe epilepsy (TLE), one of the most common pharmaco-resistant epilepsies, is associated with pathology of paralimbic brain regions, particularly in the mesiotemporal lobe. Cognitive dysfunction in TLE is frequent, and particularly affects episodic memory. Crucially, these difficulties challenge the quality of life of patients, sometimes more than seizures, underscoring the need to assess neural processes of cognitive dysfunction in TLE to improve patient management. Our work harnessed a novel conceptual and analytical approach to assess spatial gradients of microstructural differentiation between cortical areas based on high-resolution MRI analysis. Gradients track region-to-region variations in intracortical lamination and myeloarchitecture, serving as a system-level measure of structural and functional reorganization. Comparing cortex-wide microstructural gradients between 21 patients and 35 healthy controls, we observed a reorganization of this gradient in TLE driven by reduced microstructural differentiation between paralimbic cortices and the remaining cortex with marked abnormalities in ipsilateral temporopolar and dorsolateral prefrontal regions. Findings were replicated in an independent cohort. Using an independent post-mortem dataset, we observed that in vivo findings reflected topographical variations in cortical cytoarchitecture. We indeed found that macroscale changes in microstructural differentiation in TLE reflected increased similarity of paralimbic and primary sensory/motor regions. Disease-related transcriptomics could furthermore show specificity of our findings to TLE over other common epilepsy syndromes. Finally, microstructural dedifferentiation was associated with cognitive network reorganization seen during an episodic memory functional MRI paradigm and correlated with interindividual differences in task accuracy. Collectively, our findings showing a pattern of reduced microarchitectural differentiation between paralimbic regions and the remaining cortex provide a structurally-grounded explanation for large-scale functional network reorganization and cognitive dysfunction characteristic of TLE.

A convergent structure-function substrate of cognitive imbalances in autism.

BACKGROUND: Autism spectrum disorder (ASD) is a common neurodevelopmental diagnosis showing substantial phenotypic heterogeneity. A leading example can be found in verbal and nonverbal cognitive skills, which vary from elevated to impaired compared with neurotypical individuals. Moreover, deficits in verbal profiles often coexist with normal or superior performance in the nonverbal domain. METHODS: To study brain substrates underlying cognitive imbalance in ASD, we capitalized categorical and dimensional IQ profiling as well as multimodal neuroimaging. RESULTS: IQ analyses revealed a marked verbal to nonverbal IQ imbalance in ASD across 2 datasets (Dataset-1: 155 ASD, 151 controls; Dataset-2: 270 ASD, 490 controls). Neuroimaging analysis in Dataset-1 revealed a structure-function substrate of cognitive imbalance, characterized by atypical cortical thickening and altered functional integration of language networks alongside sensory and higher cognitive areas. CONCLUSION: Although verbal and nonverbal intelligence have been considered as specifiers unrelated to autism diagnosis, our results indicate that intelligence disparities are accentuated in ASD and reflected by a consistent structure-function substrate affecting multiple brain networks. Our findings motivate the incorporation of cognitive imbalances in future autism research, which may help to parse the phenotypic heterogeneity and inform intervention-oriented subtyping in ASD.

Long-range functional connections mirror and link microarchitectural and cognitive hierarchies in the human brain.

BACKGROUND: Higher-order cognition is hypothesized to be implemented via distributed cortical networks that are linked via long-range connections. However, it is unknown how computational advantages of long-range connections reflect cortical microstructure and microcircuitry. METHODS: We investigated this question by (i) profiling long-range cortical connectivity using resting-state functional magnetic resonance imaging (MRI) and cortico-cortical geodesic distance mapping, (ii) assessing how long-range connections reflect local brain microarchitecture, and (iii) examining the microarchitectural similarity of regions connected through long-range connections. RESULTS: Analysis of 2 independent datasets indicated that sensory/motor areas had more clustered short-range connections, while transmodal association systems hosted distributed, long-range connections. Meta-analytical decoding suggested that this topographical difference mirrored shifts in cognitive function, from perception/action towards emotional/social processing. Analysis of myelin-sensitive in vivo MRI as well as postmortem histology and transcriptomics datasets established that gradients in functional connectivity distance are paralleled by those present in cortical microarchitecture. Notably, long-range connections were found to link spatially remote regions of association cortex with an unexpectedly similar microarchitecture. CONCLUSIONS: By mapping covarying topographies of long-range functional connections and cortical microcircuits, the current work provides insights into structure-function relations in human neocortex.

Two-dimensional liquid chromatography measurement of meropenem concentration in synovial fluid of patients with periprosthetic joint infection.

Periprosthetic joint infection (PJI) is a catastrophic complication following joint replacement surgery. One potential treatment approach for PJI could be the combination of one-stage revision and intra-articular infusion of antibiotics. Meropenem is one of the commonly used intra-articular antibiotics in our institution. Determining the concentration of meropenem in the joint cavity could be crucial for optimizing its local application, effectively eradicating biofilm infection, and improving PJI treatment outcomes. In this study, we developed a simple, precise, and accurate method of two-dimensional liquid chromatography (2D-LC) for determining the concentration of meropenem in human synovial fluid. The method was then validated based on the guidelines of the Food and Drug Administration and the Chinese Pharmacopoeia. Meropenem showed good linearity in the range of 0.31-25.01 µg/mL (r ≥ .999). Selectivity, intra-day and inter-day precision and accuracy, extraction recovery, and stability validation results were all within the acceptance range. This method has been successfully applied to the determination of synovial fluid samples from PJI patients, providing a useful detection method for meropenem therapeutic drug monitoring (TDM) in PJI patients.

Shifts in structural connectome organization in the limbic and sensory systems of patients with episodic migraine.

Migraine is a complex neurological condition characterized by recurrent headaches, which is often accompanied by various neurological symptoms. Magnetic resonance imaging (MRI) is a powerful tool for investigating whole-brain connectivity patterns; however, systematic assessment of structural connectome organization has rarely been performed. In the present study, we aimed to examine the changes in structural connectivity in patients with episodic migraines using diffusion MRI. First, we computed structural connectivity using diffusion MRI tractography, after which we applied dimensionality reduction techniques to the structural connectivity and generated three low-dimensional eigenvectors. We subsequently calculated the manifold eccentricity, defined as the Euclidean distance between each data point and the center of the data in the manifold space. We then compared the manifold eccentricity between patients with migraines and healthy controls, revealing significant between-group differences in the orbitofrontal cortex, temporal pole, and sensory/motor regions. Between-group differences in subcortico-cortical connectivity further revealed significant changes in the amygdala, accumbens, and caudate nuclei. Finally, supervised machine learning effectively classified patients with migraines and healthy controls using cortical and subcortical structural connectivity features, highlighting the importance of the orbitofrontal and sensory cortices, in addition to the caudate, in distinguishing between the groups. Our findings confirmed that episodic migraine is related to the structural connectome changes in the limbic and sensory systems, suggesting its potential utility as a diagnostic marker for migraine.

[Evidence map of clinical research on Chinese patent medicines for post-acute myocardial infarction heart failure].

An evidence map was established to comprehensively sort out the clinical research in the treatment of post-acute myocardial infarction heart failure(P-AMI-HF) with Chinese patent medicines, so as to reveal the distribution of evidence in this field. CNKI, Wanfang, VIP, SinoMed, PubMed, Cochrane Library, and EMbase were searched for the randomized controlled trial(RCT), systematic reviews/Meta-analysis, and guidelines/consensus in this field. The evidence was analyzed and displayed in the form of a combination of text, charts, bubble charts, and bar charts, and the quality of RCT, systematic reviews/Meta-analysis, and guidelines/consensus were evaluated by RoB 1.0, AMSTAR2, and AGREE Ⅱ, respectively. A total of 163 RCTs, 4 systematic reviews/Meta-analysis, 1 network Meta-analysis, 2 observational studies, and 5 guidelines/consensus were included. In recent years, the total number of publications in this field has shown an upward trend. There were a variety of Chinese patent medicines in the treatment of P-AMI-HF, among which Shenfu Injection received the most attention. The clinical RCT and systematic reviews/Meta-analysis generally had poor quality, and the RCT mostly had a small size, a single center, and a short cycle. The outcome indicators mainly included cardiac function indicators, myocardial injury markers, total response rate, hemodynamic indicators, and safety indicators, while the characteristic efficacy indicators of TCM received insufficient attention. The development processes of some guidelines/consensus lack standardization, which compromised their authority and rationality. Chinese patent medicines have advantages in the treatment of P-AMI-HF, while there are also problems, which remain to be solved by more high-quality evidence. That is, more large-sample and multi-center clinical studies should be carried out in the future, and the formulation process of relevant systematic reviews/Meta-analysis and guideline/consensus should be standardized and the quality of evidence should be improved. In this way, the effectiveness and safety of Chinese patent medicines in the treatment of P-AMI-HF can be explored.

[Network Meta-analysis of Chinese patent medicine in treatment of heart failure with preserved ejection fraction].

This study systematically evaluated the efficacy and safety of different Chinese patent medicines combined with conventional western medicine in the treatment of heart failure with preserved ejection fraction(HFpEF) and ranked for the drug selection. Randomized controlled trial(RCT) on Chinese patent medicines in treatment of HFpEF were obtained from the CNKI, Wanfang, VIP, SinoMed, PubMed, Cochrane Library, EMbase, Web of Science, and other databases from the inception to October 9, 2022. The included RCT was quantitatively analyzed using gemtc and rjags packages of R software for the network Meta-analysis. 74 RCTs were included, with a total of 7 192 patients enrolled, involving 11 different Chinese patent medicines(Shenfu Injection, Shenmai Injection, Qili Qiangxin Capsules, Shexiang Baoxin Pills, Xuezhikang Capsules, Salvia Miltiorrhiza Polyphenols Injection, Tanshinone Ⅱ_A Sulfonate Injection, Xinmailong Injection, Yangxinshi Tablets, Qishen Yiqi Dripping Pills, and Yixinshu Capsules). The results of network Meta-analysis are shown as followed.(1)In terms of improving clinical effective rate, for injection preparations, Xinmailong Injection + conventional western medicine was recommended. while for oral preparations, Shexiang Baoxin Pills + conventional western medicine, Qishen Yiqi Dripping Pills + conventional western medicine, and Qili Qiangxin Capsules + conventional western medicine were preferred.(2)In terms of improving the mitral ratio of peak early to late diastolic filling velocity(E/A), for injection preparations, Shenmai Injection + Salvia Miltiorrhiza Polyphenols Injection + conventional western medicine, Shenmai Injection + conventional western medicine, Shenfu Injection + conventional western medicine were preferred. While for oral preparations, Yixinshu Capsules + conventional western medicine was preferred.(3)In terms of reducing the ratio of early diastolic mitral inflow to early diastolic mitral annular velocity(E/e'), Shenfu Injection + conventional western medicine could be used as injection preparation, and Qili Qiangxin Capsules + conventional western medicine, Qishen Yiqi Dripping Pills + conventional western medicine for oral preparations.(4)In terms of improving 6-minute walking trail(6MWT), the injection preparations such as Shenmai Injection + conventional western medicine, Xinmailong Injection + conventional western medicine were suitable, while oral preparations like Qishen Yiqi Dripping Pills + conventional western medicine, Qili Qiangxin Capsules + conventional western medicine were recommended.(5)In terms of reducing N-terminal pro B-type natriuretic peptide(NT-proBNP), Qili Qiangxin Capsules + conventional western medicine were preferred.(6)In terms of reducing B-type natriuretic peptide(BNP), Xinmailong Injection + conventional western medicine could be used for injection preparation and Qili Qiangxin Capsules + conventional western medicine can be used for oral preparation. In terms of adverse drug reactions, there was no significant difference between Chinese patent medicine combined with conventional western conventional and traditional western medicine alone. The results showe that Chinese patent medicine combined with conventional western medicine in treating HFpEF is superior to conventional western medicine alone in reducing clinical symptoms, improving cardiac function, and improving exercise tolerance, which also has good drug safety. However, the existing evidence is still limited by the quality and quantity of included studies, so the above conclusion requires further validation through more prospective RCT.

Whole-brain functional gradients reveal cortical and subcortical alterations in patients with episodic migraine.

Migraine is a type of headache with multiple neurological symptoms. Prior neuroimaging studies in patients with migraine based on functional magnetic resonance imaging have found regional as well as network-level alterations in brain function. Here, we expand on prior studies by establishing whole-brain functional connectivity patterns in patients with migraine using dimensionality reduction techniques. We studied functional brain connectivity in 50 patients with episodic migraine and sex- and age-matched healthy controls. Using dimensionality reduction techniques that project high-dimensional functional connectivity onto low-dimensional representations (i.e., eigenvectors), we found significant between-group differences in the eigenvectors between patients with migraine and healthy controls, particularly in the sensory/motor and limbic cortices. Furthermore, we assessed between-group differences in subcortical connectivity with subcortical weighted manifolds defined by subcortico-cortical connectivity multiplied by cortical eigenvectors and revealed significant alterations in the amygdala. Finally, leveraging supervised machine learning, we moderately predicted headache frequency using cortical and subcortical functional connectivity features, again indicating that sensory and limbic regions play a particularly important role in predicting migraine frequency. Our study confirmed that migraine is a hierarchical disease of the brain that shows alterations along the sensory-limbic axis, and therefore, the functional connectivity in these areas could be a useful marker to investigate migraine symptomatology.

High power single-frequency 1112†nm laser by an insertable Nd:YAG/YAG bonded monolithic planar ring oscillator.

A high power single-frequency operation at 1112 nm with novel insertable monolithic planar ring oscillator based on a Nd:YAG/YAG bonded crystal is proposed. In a proof-of-principle experiment, a finely designed coating on the output surface is carried out to ensure single-wavelength oscillation at 1112 nm, together with a half-wave plate and a Tb3Ga5O12 crystal inserted in the open space of the bonded block to realize the unidirectional operation with power scalability. Consequently, the single-frequency laser delivers an output power of 3.9 W at 1112.3 nm with a slope efficiency of 58.6% and an optical-to-optical efficiency of 17.7%. The power fluctuation is measured to be within ± 0.26% over 20 min, and the laser linewidth is estimated to be 4.15 MHz (Δλ = 0.017 pm).

Sub-pm linewidth, high pulse energy, high beam quality microsecond-pulse Ti:sapphire laser at 766.699†nm.

In this letter, a sub-pm linewidth, high pulse energy and high beam quality microsecond-pulse 766.699 nm Ti:sapphire laser pumped by a frequency-doubled Nd:YAG laser is demonstrated. At an incident pump energy of 824 mJ, the maximum output energy of 132.5 mJ at 766.699 nm with linewidth of 0.66 pm and a pulse width of 100 µs is achieved at a repetition rate of 5 Hz. To the best of our knowledge, this is the highest pulse energy at 766.699 nm with pulse width of hundred micro-seconds for a Ti:sapphire laser. The beam quality factor M2 is measured to be 1.21. It could be precisely tuned from 766.623 to 766.755 nm with a tuning resolution of 0.8 pm. The wavelength stability is measured to be less than ±0.7 pm over 30 min. The sub-pm linewidth, high pulse energy and high beam quality Ti:sapphire laser at 766.699 nm can be used to create a polychromatic laser guide star together with a home-made 589 nm laser in the mesospheric sodium and potassium layer for the tip-tilt correction resulting in the near-diffraction limited imagery on a large telescope.

Atypical intrinsic neural timescales in temporal lobe epilepsy.

OBJECTIVE: Temporal lobe epilepsy (TLE) is the most common pharmacoresistant epilepsy in adults. Here we profiled local neural function in TLE in vivo, building on prior evidence that has identified widespread structural alterations. Using resting-state functional magnetic resonance imaging (rs-fMRI), we mapped the whole-brain intrinsic neural timescales (INT), which reflect temporal hierarchies of neural processing. Parallel analysis of structural and diffusion MRI data examined associations with TLE-related structural compromise. Finally, we evaluated the clinical utility of INT. METHODS: We studied 46 patients with TLE and 44 healthy controls from two independent sites, and mapped INT changes in patients relative to controls across hippocampal, subcortical, and neocortical regions. We examined region-specific associations to structural alterations and explored the effects of age and epilepsy duration. Supervised machine learning assessed the utility of INT for identifying patients with TLE vs controls and left- vs right-sided seizure onset. RESULTS: Relative to controls, TLE showed marked INT reductions across multiple regions bilaterally, indexing faster changing resting activity, with strongest effects in the ipsilateral medial and lateral temporal regions, and bilateral sensorimotor cortices as well as thalamus and hippocampus. Findings were similar, albeit with reduced effect sizes, when correcting for structural alterations. INT reductions in TLE increased with advancing disease duration, yet findings differed from the aging effects seen in controls. INT-derived classifiers discriminated patients vs controls (balanced accuracy, 5-fold: 76% ± 2.65%; cross-site, 72%-83%) and lateralized the focus in TLE (balanced accuracy, 5-fold: 96% ± 2.10%; cross-site, 95%-97%), with high accuracy and cross-site generalizability. Findings were consistent across both acquisition sites and robust when controlling for motion and several methodological confounds. SIGNIFICANCE: Our findings demonstrate atypical macroscale function in TLE in a topography that extends beyond mesiotemporal epicenters. INT measurements can assist in TLE diagnosis, seizure focus lateralization, and monitoring of disease progression, which emphasizes promising clinical utility.