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Koike, S.

Publications and source records attributed to Koike, S..

At least 19 recordsLinked to original sources

High-Frequency Activity Encodes the Temporal Dynamics of Hierarchical Prediction Errors in Humans: An Electrocorticography Study

Prediction error refers to the discrepancy between expected and actual sensory input. Its hierarchical organization has been demonstrated through decomposed brain responses in the local-global paradigm, where temporal regularities are established locally at individual stimulus transitions and globally across multi-tone sequence structures. In macaques and marmosets, local and global prediction-error signals have both been found in high-frequency oscillations (60-150 Hz) recorded with ECoG. In humans, however, these signals have primarily been observed in a lower frequency range (30-100 Hz) using EEG. Here, we recorded human ECoG to achieve higher signal fidelity, enabling examination of neural oscillations above 100 Hz (high-frequency activity, HFA), which are believed to be closely linked to local spiking activity. Eight participants listened to auditory sequences that either followed their local and global regularities (local and global standards) or violated them (local and global deviants). Robust HFA responses were observed for the local deviants, but these responses were reduced when the deviants were expected based on the global regularity, indicating both levels of prediction-error processes contribute to the observed activity. Importantly, these HFA responses could be decomposed into two subcomponents: an early component reflecting local prediction-error signals localized to lateral auditory regions, and a late component reflecting global prediction-error signals prominent in both lateral auditory and frontal cortices. Together, these findings demonstrate that neural oscillations above 100 Hz encode hierarchical prediction errors not only in non-human primates but also in humans.

neuroscience↗

CGK733 binds to adenine nucleotide translocator 2 and modulates mitochondrial function and protein translation

Chemical genetics is a powerful strategy for dissecting biological mechanisms, and a crucial step in this approach is to identify the molecular target responsible for a compounds activity. CGK733, a compound with anti-proliferative activity, was once reported as an ATM/ATR inhibitor, although this activity has been debated, and its target and mode of action have remained unclear. Here, we show that CGK733 inhibits cell-cycle progression and global protein translation. Affinity purification identified adenine nucleotide translocator 2 (ANT2) as the primary target. CGK733 blocked ATP export from mitochondria and induced proton leak, thereby shifting ATP production from mitochondrial respiration to glycolysis and perturbing the TCA cycle. These mitochondrial alterations were accompanied by inactivation of the mTOR pathway and mild activation of the integrated stress response, resulting in translational inhibition. Collectively, our findings demonstrate that CGK733 acts mainly through ANT2-dependent mitochondrial modulation, revealing a mechanistic link between mitochondrial bioenergetics and translational control.

biochemistry↗

Unsupervised feature computation-based feature selection robustly extracted resting-state functional connectivity patterns related to mental disorders

Research on biomarkers for predicting psychiatric disorders from resting-state functional connectivity (FC) is advancing. While the focus has primarily been on the discriminative performance of biomarkers by machine learning, identification of abnormal FCs in psychiatric disorders has often been treated as a secondary goal. However, it is crucial to investigate the effect size and robustness of the selected FCs because they can be used as potential targets of neurofeedback training or transcranial magnetic stimulation therapy. Here, we incorporated approximately 5,000 runs of resting-state functional magnetic resonance imaging from six datasets, including individuals with three different psychiatric disorders (major depressive disorder [MDD], schizophrenia [SCZ], and autism spectrum disorder [ASD]). We demonstrated that an unsupervised feature-computation-based feature selection method can robustly extract FCs related to psychiatric disorders compared to other conventional supervised feature selection methods. We found that our proposed method robustly extracted FCs with larger effect sizes from the validation dataset compared to different types of feature selection methods based on supervised learning for MDD (Cohens d = 0.40 vs. 0.25), SCZ (0.37 vs. 0.28), and ASD (0.17 vs. 0.16). We found 78, 69, and 81 essential FCs for MDD, SCZ, and ASD, respectively, and these FCs were mainly thalamic and motor network FCs. The current study showed that the unsupervised feature-computation-based feature selection method robustly identified abnormal FCs in psychiatric disorders consistently across datasets. The discovery of such robust FCs will contribute to understanding neural mechanisms as abnormal brain signatures in psychiatric disorders. Furthermore, this finding can aid in developing precise therapeutic interventions, such as neurofeedback training or transcranial magnetic stimulation therapy.

neuroscience↗

Chronic social defeat causes dysregulation of systemic glucose metabolism via the cerebellar fastigial nucleus

Chronic psychological stress leads to hyperglycemia through the endocrine and sympathetic nervous systems, which contributes to the development of type II diabetes mellitus (T2DM). Higher plasma corticosteroids after stress is one well-established driver of insulin resistance in peripheral tissues. However, previous studies have indicated that only a fraction of patients with depression and post-traumatic disorder (PTSD) who develop T2DM exhibit hypocortisolism, so corticosteroids do not fully explain psychological stress-induced T2DM. Here, we find that chronic social defeat stress (CSDS) in mice enhances gluconeogenesis, which is accompanied by a decrease in plasma insulin, an increase in plasma catecholamines, and a drop in plasma corticosterone levels. We further reveal that these metabolic and endocrinological changes are mediated by the activation of neurons projecting from the cerebellar fastigial nucleus (FN) to the medullary parasolitary nucleus (PSol). These neurons are crucial in shifting the bodys primary energy source from glucose to lipids. Additionally, data from patients with depression reveal correlations between the presence of cerebellar abnormalities and both worsening depressive symptoms and elevated HbA1c levels. These findings highlight a previously unappreciated role of the cerebellum in metabolic regulation and its importance as a potential therapeutic target in depression, PTSD, and similar psychological disorders.

neuroscience↗

Biological sex and BMI influence the longitudinal evolution of adolescent and young adult MRI-visible perivascular spaces

Background and PurposeAn association recently emerged between magnetic resonance imaging (MRI)-visible perivascular spaces (MV-PVS) with intracerebral solute clearance and neuroinflammation, in adults. However, it is unknown how MV-PVS change throughout adolescence and what factors influence MV-PVS volume and morphology. This study assesses the temporal evolution of MV-PVS volume in adolescents and young adults, and secondarily evaluates the relationship between MV-PVS, age, sex, and body mass index (BMI). Materials and MethodsThis analysis included a 783 participant cohort from the longitudinal multicenter National Consortium on Alcohol and Neurodevelopment in Adolescence study that involved up to 6 imaging visits spanning 5 years. Healthy adolescents aged 12-21 years at study entry with at least two MRI scans were included. The primary outcome was mean MV-PVS volume (mm3/white matter cm3). ResultsOn average, males had greater MV-PVS volume at all ages compared to females. A linear mixed-effect model for MV-PVS volume was performed. Mean BMI and increases in a persons BMI were associated with increases in MV-PVS volume over time. In females only, changes in BMI correlated with MV-PVS volume. One unit increase in BMI above a persons average BMI was associated with a 0.021 mm3/cm3 increase in MV-PVS volume (p<0.001). ConclusionThis longitudinal study showed sex differences in MV-PVS features during adolescence and young adulthood. Importantly, we report that increases in BMI from a persons mean BMI are associated with increases in MV-PVS volume in females only. These findings suggest a potential link between MV-PVS, sex, and BMI that warrants future study.

neuroscience↗

Computational Mechanisms of Neuroimaging Biomarkers Uncovered by Multicenter Resting-State fMRI Connectivity Variation Profile

Resting-state functional connectivity (rsFC) is increasingly used to develop biomarkers for psychiatric disorders. Despite progress, development of the reliable and practical FC biomarker remains an unmet goal, particularly one that is clinically predictive at the individual level with generalizability, robustness, and accuracy. In this study, we propose a new approach to profile each connectivity from diverse perspective, encompassing not only disorder-related differences but also disorder-unrelated variations attributed to individual difference, within-subject across-runs, imaging protocol, and scanner factors. By leveraging over 1500 runs of 10-minute resting-state data from 84 traveling-subjects across 29 sites and 900 participants of the case-control study with three psychiatric disorders, the disorder-related and disorder-unrelated FC variations were estimated for each individual FC. Using the FC profile information, we evaluated the effects of the disorder-related and disorder-unrelated variations on the output of the multi-connectivity biomarker trained with ensemble sparse classifiers and generalizable to the multicenter data. Our analysis revealed hierarchical variations in individual functional connectivity, ranging from within-subject across-run variations, individual differences, disease effects, inter-scanner discrepancies, and protocol differences, which were drastically inverted by the sparse machine-learning algorithm. We found this inversion mainly attributed to suppression of both individual difference and within-subject across-runs variations relative to the disorder-related difference by weighted-averaging of the selected FCs and ensemble computing. This comprehensive approach will provide an analytical tool to delineate future directions for developing reliable individual-level biomarkers.

neuroscience↗

Amelioration of age-related cognitive decline and anxiety in mice by Centella asiatica extract varies by sex, dose and mode of administration.

We have previously reported that a water extract (CAW) of the Ayurvedic plant Centella asiatica administered in drinking water can improve cognitive deficits in mouse models of aging and neurodegenerative diseases. Here we compared the effects of CAW administered in drinking water or the diet on cognition, measures of anxiety and depression-like behavior in healthy aged mice. Three- and eighteen-month-old male and female C57BL6 mice were administered rodent AIN-93M diet containing CAW (0, 0.2, 0.5 or 1% w/w) to provide 0, 200 mg/kg/d, 500 mg/kg/d or 1000 mg/kg/d for a total of 5 weeks. An additional group of eighteen-month-old mice were treated with CAW (10 mg/mL) in their drinking water for a total of five weeks to deliver the same exposure of CAW as the highest dietary dose (1000 mg/kg/d). CAW doses delivered were calculated based on food and water consumption measured in previous experiments. In the fourth and fifth weeks, mice underwent behavioral testing of cognition, anxiety and depression (n=12 of each sex per treatment group in each test). Aged mice of both sexes showed cognitive deficits relative to young mice while only female aged mice showed increased anxiety compared to the young female mice and no differences in depression were observed between the different ages. CAW (1000 mg/kg/d) in the drinking water improved deficits in aged mice in learning, executive function and recognition memory in both sexes and attenuated the increased measures of anxiety observed in the aged female mice. However, CAW in the diet only improved executive function in aged mice at the highest dose (1000 mg/kg/d) in both sexes and did so less robustly than when given in the water. There were no effects of CAW on depression-like behavior in aged animals regardless of whether it was administered in the diet or the water. These results suggest that CAW can ameliorate age-related changes in measures of anxiety and cognition and that the mode of administration is important for the effects of CAW on resilience to these age-related changes.

animal behavior and cognition↗

Actin dynamics switches two distinct modes of endosomal fusion in yolk sac visceral endoderm cells

Membranes undergo various patterns of deformation during vesicle fusion, but how this membrane deformation is regulated and contributes to fusion remains unknown. In this study, we developed a new method of observing the fusion of individual late endosomes and lysosomes by using yolk sac visceral endoderm cells that have huge endocytic vesicles. We found that there were two distinct fusion modes that were differently regulated. In homotypic fusion, two late endosomes fused quickly, whereas in heterotypic fusion they fused to lysosomes slowly. Mathematical modeling showed that vesicle size is a critical determinant of these fusion types and that membrane fluctuation forces can overcome the vesicle size effects. We found that actin filaments were bound to late endosomes and forces derived from dynamic actin remodeling were necessary for quick fusion during homotypic fusion. Furthermore, cofilin played a role in endocytic fusion by regulating actin turnover. These data suggest that actin promotes vesicle fusion for efficient membrane trafficking in visceral endoderm cells.

cell biology↗

Dissecting Mismatch Negativity: Early and Late Subcomponents for Detecting Deviants in Local and Global Sequence Regularities

Mismatch negativity (MMN) is commonly recognized as a neural signal of prediction error evoked by deviants in the expected pattern of sensory input. Studies show that MMN diminishes when a sequence pattern becomes more predictable over a longer timescale. This implies that MMN is comprised of multiple subcomponents, each responding to different levels of temporal regularities. To probe the hypothesized subcomponents in MMN, we record human electroencephalography during an auditory local-global oddball paradigm where the tone-to-tone transition probability (local regularity) and the overall sequence probability (global regularity) are manipulated to control temporal predictabilities at two hierarchical levels. We find that the size of MMN is correlated with both probabilities and the spatiotemporal structure of MMN can be decomposed into two distinct subcomponents. Both subcomponents appear as negative waveforms which peak early in the central-frontal area and late in a more frontal area, respectively. With a quantitative predictive coding model, we map the early and late subcomponents to the prediction errors that are tied to local and global regularities, respectively. Our study highlights the hierarchical complexity of MMN and offers an experimental and analytical platform for developing a multi-tiered neural marker, applicable in clinical settings.

neuroscience↗

Crossmodal Hierarchical Predictive Coding for Audiovisual Sequences in Human Brain

Predictive-coding theory proposes that the brain actively predicts sensory inputs based on prior knowledge. While this theory has been extensively researched within individual sensory modalities, there is a crucial need for empirical evidence supporting hierarchical predictive processing across different modalities to further generalize the theory. Here, we examine how crossmodal knowledge is represented and learned in the brain by identifying the hierarchical networks underlying crossmodal predictions when information of one sensory modality leads to a prediction in another modality. We record electroencephalogram (EEG) in humans during a crossmodal audiovisual local-global oddball paradigm, in which the predictability of transitions between tones and images are manipulated at two hierarchical levels: stimulus-to-stimulus transition (local level) and multi-stimulus sequence structure (global level). With a model-fitting approach, we decompose the EEG data using three distinct predictive-coding models: one with no audiovisual integration, one with audiovisual integration at the global level, and one with audiovisual integration at both the local and global levels. The best-fitting model demonstrates that audiovisual integration occurs at both levels. This highlights a convergence of auditory and visual information to construct crossmodal predictions, even in the more basic interactions that occur between individual stimuli. Furthermore, we reveal the spatio-spectro-temporal signatures of prediction-error signals across hierarchies and modalities, and show that auditory and visual prediction-error signals are progressively redirected to the central-parietal area of the brain as learning progresses. Our findings unveil a crossmodal predictive coding mechanism, where the unimodal framework is implemented through more distributed brain networks to process hierarchical crossmodal knowledge.

neuroscience↗

Organelle landscape analysis using a multi-parametric particle-based method

Organelles have unique structures and molecular compositions for their functions and have been classified accordingly. However, many organelles are heterogeneous and in the process of maturation and differentiation. Because traditional methods have a limited number of parameters and spatial resolution, they struggle to capture the heterogeneous landscapes of organelles. Here, we present a method for multi-parametric particle-based analysis of organelles. After disrupting cells, fluorescence microscopy images of organelle particles labeled with six to eight different organelle markers were obtained, and their multi-dimensional data were represented in intuitive two-dimensional UMAP (uniform manifold approximation and projection) spaces. This method enabled visualization of landscapes of seven major organelles as well as the transitional states of endocytic organelles directed to the recycling and degradation pathways. Furthermore, endoplasmic reticulum-mitochondria contact sites were detected in these maps. Our proposed method successfully detects a wide array of organelles simultaneously, enabling the analysis of heterogeneous organelle landscapes.

cell biology↗

Comprehensive analysis of nasal IgA antibodies induced by intranasal administration of the SARS-CoV-2 spike protein

Intranasal vaccination is an attractive strategy for preventing COVID-19 disease as it stimulates the production of multimeric secretory immunoglobulin A (IgA), the predominant antibody isotype in the mucosal immune system, at the target site of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) entry. Currently, intranasal vaccine efficacy is evaluated based on the measurement of polyclonal antibody titers in nasal lavage fluid. However, how individual multimeric secretory IgA protects the mucosa from SARS-CoV-2 infection remains to be elucidated. To understand the precise contribution and molecular nature of multimeric secretory IgA induced by intranasal vaccines, we developed 99 monoclonal IgA clones from nasal mucosa and 114 monoclonal IgA or IgG clones from nonmucosal tissues of mice that were intranasally immunized with the SARS-CoV-2 spike protein. The nonmucosal IgA clones exhibited shared origins and common and unique somatic mutations with the related nasal IgA clones, indicating that the antigen-specific plasma cells in the nonmucosal tissues originated from B cells stimulated at the nasal mucosa. Comparing the spike protein binding reactivity, angiotensin-converting enzyme-2-blocking and in vitro SARS-CoV-2 virus neutralization of monomeric and multimeric secretory IgA pairs recognizing different epitopes showed that even non-neutralizing monomeric IgAs, which represents 70% of the nasal IgA repertoire, can protect against SARS-CoV-2 infection when expressed as multimeric secretory IgAs. We also demonstrated that the intranasal administration of multimeric secretory IgA delivered as prophylaxis in the hamster model reduced infection-induced weight loss. Our investigation is the first to demonstrate the function of nasal IgA at the monoclonal level, showing that nasal immunization can provide effective immunity against SARS-CoV-2 by inducing multimeric secretory IgAs at the target site of the virus infection.

immunology↗

Normative modeling of brain morphometry in Clinical High-Risk for Psychosis

ImportanceThe lack of robust neuroanatomical markers of psychosis risk has been traditionally attributed to heterogeneity. A complementary hypothesis is that variation in neuroanatomical measures in the majority of individuals at psychosis risk may be nested within the range observed in healthy individuals. ObjectiveTo quantify deviations from the normative range of neuroanatomical variation in individuals at clinical high-risk for psychosis (CHR-P) and evaluate their overlap with healthy variation and their association with positive symptoms, cognition, and conversion to a psychotic disorder. Design, Setting, and ParticipantsClinical, IQ and FreeSurfer-derived regional measures of cortical thickness (CT), cortical surface area (SA), and subcortical volume (SV) from 1,340 CHR-P individuals [47.09% female; mean age: 20.75 (4.74) years] and 1,237 healthy individuals [44.70% female; mean age: 22.32 (4.95) years] from 29 international sites participating in the ENIGMA Clinical High Risk for Psychosis Working Group. Main Outcomes and MeasuresFor each regional morphometric measure, z-scores were computed that index the degree of deviation from the normative means of that measure in a healthy reference population (N=37,407). Average deviation scores (ADS) for CT, SA, SV, and globally across all measures (G) were generated by averaging the respective regional z-scores. Regression analyses were used to quantify the association of deviation scores with clinical severity and cognition and two-proportion z-tests to identify case-control differences in the proportion of individuals with infranormal (z<-1.96) or supranormal (z>1.96) scores. ResultsCHR-P and healthy individuals overlapped in the distributions of the observed values, regional z-scores, and all ADS vales. The proportion of CHR-P individuals with infranormal or supranormal values in any metric was low (<12%) and similar to that of healthy individuals. CHR-P individuals who converted to psychosis compared to those who did not convert had a higher percentage of infranormal values in temporal regions (5-7% vs 0.9-1.4%). In the CHR-P group, only the ADSSA showed significant but weak associations (|{beta}|<0.09; PFDR<0.05) with positive symptoms and IQ. Conclusions and RelevanceThe study findings challenge the usefulness of macroscale neuromorphometric measures as diagnostic biomarkers of psychosis risk and suggest that such measures do not provide an adequate explanation for psychosis risk. Key pointsO_ST_ABSQuestionC_ST_ABSIs the risk of psychosis associated with brain morphometric changes that deviate significantly from healthy variation? FindingsIn this study of 1340 individuals high-risk for psychosis (CHR-P) and 1237 healthy participants, individual-level variation in macroscale neuromorphometric measures of the CHR-P group was largely nested within healthy variation and was not associated with the severity of positive psychotic symptoms or conversion to a psychotic disorder. MeaningThe findings suggest the macroscale neuromorphometric measures have limited utility as diagnostic biomarkers of psychosis risk.

neuroscience↗

Border-associated macrophages transventricularly infiltrate the early embryonic cerebral wall to differentiate into microglia

The relationships between microglia and macrophages, especially their lineage segregation outside the yolk sac, have been recently explored, providing a model in which a conversion from macrophages seeds microglia during brain development. However, spatiotemporal evidence to support such microglial seeding and to explain how it occurs has not been obtained. By cell tracking via slice culture, intravital imaging, and Flash tag-mediated labeling, we found that a group of intraventricular macrophages belonging to border-associated macrophages (BAMs), which were abundantly observed along the inner surface of the mouse cerebral wall at embryonic day 12, frequently entered the brain wall. Immunohistochemistry of the tracked cells showed that postinfiltrative BAMs acquired microglial properties while losing a macrophage phenotype. We also found that the intraventricular BAMs were supplied transepithelially from the roof plate. Thus, this study demonstrates that the "roof plate[->]ventricle[->]cerebral wall" route is an essential path for microglial colonization into the embryonic mouse brain.

neuroscience↗

Paracrine signaling by pancreatic delta cells determines the glycemic set point in mice

Pancreatic islets contain several endocrine cell types that coordinate to maintain blood glucose homeostasis. While {beta} and cells are thought to be the main drivers of glucose homeostasis through insulin and glucagon secretion respectively, the contribution of {delta} cells and somatostatin (SST) secretion to establishing the glycemic set point remains unresolved. Here we remove local SST signaling from {delta} cells within the pancreatic islet to investigate their contribution to the glycemic set point. Our data demonstrate that ablating {delta} cells or SST leads to a sustained decrease in the glycemic set point. This coincides with a decreased glucose threshold for insulin response from {beta} cells, leading to increased insulin secretion to the same glucose challenge. In contrast, cell ablation had no effect on glycemic set point. Collectively, these data establish the physiological role of {delta} cells in determining the glycemic set point through their interaction with {beta} cells.

physiology↗

Timing of fruiting rather than topography determines the direction of vertical seed dispersal by mammals and birds

Vertical seed dispersal toward higher or lower altitudes has been recognized as one of the critical processes for plants to escape from climate change. Studies exploring vertical seed dispersal are scarce, preventing the prediction of future vegetation dynamics. In the present study, we show that the timing of fruiting, rather than topography, determines the direction of vertical seed dispersal by mammals and birds across mountains in central Japan. We found strong uphill seed dispersal of summer fruiting cherry and weak downhill seed dispersal of summer-to-autumn fruiting cherry, irrespective of mountains and animals. The ascent or descent of animals, following the altitudinal gradients in food plant phenology in the temperate zone, was considered to be a driver of the biased seed dispersal. We found that megafauna (i.e., bears) intensively dispersed seeds vertically. The results suggest that the timing of fruiting and megafauna strongly affect whether animal-dispersed temperate plants can maintain their populations under climate change.

ecology↗

Promoter activity-based case-control association study on SLC6A4 highlighting hypermethylation and altered amygdala volume in male patients with schizophrenia

Associations between altered DNA methylation of the serotonin transporter (5-HTT)-encoding gene SLC6A4 and early life adversity, mood and anxiety disorders, and amygdala reactivity have been reported. However, few studies have examined epigenetic alterations of SLC6A4 in schizophrenia (SZ). We examined CpG sites of SLC6A4, whose DNA methylation levels have been reported to be altered in bipolar disorder, using three independent cohorts of patients with SZ and age-matched controls. We found significant hypermethylation of a CpG site in SLC6A4 in male patients with SZ in all three cohorts. We showed that chronic administration of risperidone did not affect the DNA methylation status at this CpG site using common marmosets, and that in vitro DNA methylation at this CpG site diminished the promoter activity of SLC6A4. We then genotyped the 5-HTT-linked polymorphic region (5-HTTLPR) and investigated the relationship among 5-HTTLPR, DNA methylation, and amygdala volume using brain imaging data. We found that patients harboring low-activity 5-HTTLPR alleles showed hypermethylation and they showed a negative correlation between DNA methylation levels and left amygdala volumes. These results suggest that hypermethylation of the CpG site in SLC6A4 is involved in the pathophysiology of SZ, especially in male patients harboring low-activity 5-HTTLPR alleles.

genetics↗

Brain/MINDS Beyond Human Brain MRI Study: Multi-Site Harmonization for Brain Disorders Throughout the Lifespan

Psychiatric and neurological disorders are afflictions of the brain that can affect individuals throughout their lifespan. Many brain magnetic resonance imaging (MRI) studies have been conducted; however, imaging-based biomarkers are not yet well established for diagnostic and therapeutic use. This article describes an outline of the planned study, the Brain/MINDS Beyond human brain MRI project (FY2018 [~] FY2023), which aims to establish clinically-relevant imaging biomarkers with multi-site harmonization by collecting data from healthy traveling subjects (TS) at 13 research sites. Collection of data in psychiatric and neurological disorders across the lifespan is also scheduled at 13 sites, whereas designing measurement procedures, developing and analyzing neuroimaging protocols, and databasing are done at three research sites. The Harmonization protocol (HARP) was established for five high-quality 3T scanners to obtain multimodal brain images including T1 and T2-weighted, resting state and task functional and diffusion-weighted MRI. Data are preprocessed and analyzed using approaches developed by the Human Connectome Project. Preliminary results in 30 TS demonstrated cortical thickness, myelin, functional connectivity measures are comparable across 5 scanners, providing high reproducibility and sensitivity to subject-specific connectome. A total of 75 TS, as well as patients with various psychiatric and neurological disorders, are scheduled to participate in the project, allowing a mixed model statistical harmonization. The HARP protocols are publicly available online, and all the imaging, demographic and clinical information, harmonizing database will also be made available by 2024. To the best of our knowledge, this is the first project to implement a rigorous, prospective harmonization protocol with multi-site TS data. It explores intractable brain disorders across the lifespan and may help to identify the disease-specific pathophysiology and imaging biomarkers for clinical practice.

neuroscience↗