Human Brain Research Articles

Insights on Quercetin Therapeutic Potential for Neurodegenerative Diseases and its Nano-technological Perspectives.

The neurodegeneration process begins in conjunction with the aging of the neurons. It manifests in different parts of the brain as Aβ plaques, neurofibrillary tangles, Lewy bodies, Pick bodies, and other structures, which leads to progressive loss or death of neurons. Quercetin (QC) is a flavonoid compound found in fruits, tea, and other edible plants have antioxidant effects that have been studied from subcellular compartments to tissue levels in the brain. Also, quercetin has been reported to possess a neuroprotective role by decreasing oxidative stress-induced neuronal cell damage.The use of QC for neurodegenerative therapy, the existence of the blood-brain barrier (BBB) remains a significant barrier to improving the clinical effectiveness of the drug, so finding an innovative solution to develop simultaneous BBB-crossing ability of drugs for treating neurodegenerative disorders and improving neurological outcomes is crucial. The nanoparticle formulation of QC is considered beneficial and useful for its delivery through this route for the treatment of neurodegenerative diseases seems necessary. Increased QC accumulation in the brain tissue and more significant improvements in tissue and cellular levels are among the benefits of QC-involved nanostructures.

Therapeutic Potential of Myricetin in the Treatment of Neurological, Neuropsychiatric, and Neurodegenerative Disorders.

Myricetin (MC), 3,5,7,3',4',5'-hexahydroxyflavone, chemically belongs to a flavonoid category known to confer antioxidant, antimicrobial, antidiabetic, and neuroprotective effects. MC is known to suppress the generation of Reactive Oxygen Species (ROS), lipid peroxidation (MDA), and inflammatory markers. It has been reported to improve insulin function in the human brain and periphery. Besides this, it modulates several neurochemicals including glutamate, GABA, serotonin, etc. MC has been shown to reduce the expression of the enzyme Mono Amine Oxidase (MAO), which is responsible for the metabolism of monoamines. MC treatment reduces levels of plasma corticosterone and restores hippocampal BDNF (full form) protein in stressed animals. Further, MC has shown its protective effect against amyloid-beta, MPTP, rotenone, 6-OHDA, etc. suggesting its potential role against neurodegenerative disorders. The aim of the present review is to highlight the therapeutic potential of MC in the treatment of several neurological, neuropsychiatric, and neurodegenerative disorders.

Median nerve electrical stimulation improves traumatic brain injury by reducing TACR1 to inhibit nuclear factor-κB and CCL7 activation in microglia.

The existing report elucidates that median nerve electrical stimulation (MNS) plays a role in treating traumatic brain injury (TBI). Herein, we explored the mechanism of MNS in TBI. A TBI-induced coma model (skull was hit by a cylindrical impact hammer) was established in adult Sprague-Dawley rats. Microglia were isolated from newborn Sprague-Dawley rats and was injured by lipopolysaccharide (LPS; 10 ng/mL). Consciousness was assessed by sensory and motor functions. Brain tissue morphology was detected using hematoxylin-eosin staining assay. Ionized calcium binding adapter molecule 1, NeuN and tachykinin receptor 1 (TACR1) level were detected by immunohistochemical assay. Levels of pro-inflammatory and anti-inflammatory factors were measured by enzyme linked immune sorbent assay (ELISA). Levels of TACR1, C-C motif chemokine 7 (CCL7), phosphorylation (p)-P65 and P65 were assessed by quantitative real time polymerase chain reaction (qRT-PCR) and western blot. M1 markers (inducible nitric oxide synthase and CD86) and M2 markers (arginase-1 (Arg1) and chitinase 3-like 3 (YM1)) of microglia as well as the transfection efficiency of short hairpin TACR1 (shTACR1) were assessed by qRT-PCR. Immunofluorescence and flow cytometry assay were used to detect microglia morphology and neuron apoptosis. MNS reduced neuron injury and microglia activation in the TBI-induced rat coma model. MNS reversed the effects of TBI on levels of inflammation-related factors, M1/M2 microglia markers, TACR1, p-P65/P65 and CCL7 in rats. shTACR1 reversed the effects of LPS on inflammation-related factors, M1/M2 microglia markers, microglia activation, neuron apoptosis, p-P65/P65 value and CCL7 level. Our results revealed that MNS improved TBI by reducing TACR1 to inhibit nuclear factor-κB (NF-κB) and CCL7 activation in microglia.

In Vitro Blood-Brain Barrier Models for Neuroinfectious Diseases: A Narrative Review.

The blood-brain barrier (BBB) is a complex, dynamic, and adaptable barrier between the peripheral blood system and the central nervous system. While this barrier protects the brain and spinal cord from inflammation and infection, it prevents most drugs from reaching the brain tissue. With the expanding interest in the pathophysiology of BBB, the development of in vitro BBB models has dramatically evolved. However, due to the lack of a standard model, a range of experimental protocols, BBB-phenotype markers, and permeability flux markers was utilized to construct in vitro BBB models. Several neuroinfectious diseases are associated with BBB dysfunction. To conduct neuroinfectious disease research effectively, there stems a need to design representative in vitro human BBB models that mimic the BBB's functional and molecular properties. The highest necessity is for an in vitro standardised BBB model that accurately represents all the complexities of an intact brain barrier. Thus, this in-depth review aims to describe the optimization and validation parameters for building BBB models and to discuss previous research on neuroinfectious diseases that have utilized in vitro BBB models. The findings in this review may serve as a basis for more efficient optimisation, validation, and maintenance of a structurally- and functionally intact BBB model, particularly for future studies on neuroinfectious diseases.

Brain (Yakovlevian) torque direction is associated with volume asymmetry of the intracranial transverse sinuses: evidence from situs inversus totalis.

Previous research reported reversal of the prototypical brain torque in individuals with mirrored visceral topology (situs inversus totalis, SIT). Here, we investigate if typical asymmetry of the posterior intracranial venous system is also reversed in SIT and whether the direction and magnitude of this asymmetry is related to the direction and magnitude of the brain torque. Brain structural MRI images of 38 participants with SIT were compared with those of 38 matched control participants. Occipital and frontal petalia and bending were measured using a standardized procedure. In addition, representative sections of the left and right transverse sinuses were segmented, and their respective volumes determined. Participants with SIT showed general reversal of occipital and frontal petalia and occipital bending, as well as reversal of typical transverse sinus asymmetry. Transverse sinus volume was significantly correlated with several torque measures, such that the smaller transverse sinus was associated with a larger ipsilateral occipital petalia, contralateral occipital bending, and ipsilateral frontal bending. We propose an anatomical mechanism to explain occipital petalia and bending, and conclude that anatomical constraints imposed by the asymmetry of the posterior venous system provide and additional account to elucidate the formation of the human brain torque.

Psychological mechanism of language cognition to "awaken" artificial intelligence.

The study of artificial intelligence needs tracing back to the working mechanism of the human brain, and based on simulating brain cognition activity, information technology is the most widely influential technology. Language cognition is the core and foundation of human cognition. Biolinguistics' core problem about brain mechanisms (a psychological mechanism) is related to the development of human language cognition in that the cognitive process of humans is from the construction of mediation and language is the very cognitive mediation. The logical law of human language cognition algorithm is about the process of human cognitive psychology that is from the neurological stage, the psychological perception stage, and to the cognitive stage of symbols, which makes psychological certainty account for the connection from mental content to language meaning. Language cognition is where the "awakening" of artificial intelligence begins. First of all, humans produce mental images based on sensory perception and categories. The referential functions of mental images extend the human cognitive scope. Then, categorization is realized through the mediation of mental images. At the time the category is formed, the symbol is required. Language is involved in the thinking process in the cognitive stage of symbols to realize the construction of the mediation to represent the category abstracted from the concrete things. Above all, human language metacognition is realized from the subject-predicate structure that is the grammatical structure on the surface but is throughout the whole process of human rational knowledge and configures the content of rational knowledge, which is the developmental goal of "awakening" artificial intelligence. The demonstration of this proposition is conducive to providing a theoretical basis for the research of the working mechanism of the human brain stimulated by artificial intelligence. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

ZCCHC17 knockdown phenocopies Alzheimer's disease-related loss of synaptic proteins and hyperexcitability.

ZCCHC17 is a master regulator of synaptic gene expression and has recently been shown to play a role in splicing of neuronal mRNA. We previously showed that ZCCHC17 protein declines in Alzheimer's disease (AD) brain tissue before there is significant gliosis and neuronal loss, that ZCCHC17 loss partially replicates observed splicing abnormalities in AD brain tissue, and that maintenance of ZCCHC17 levels is predicted to support cognitive resilience in AD. Here, we assessed the functional consequences of reduced ZCCHC17 expression in primary cortical neuronal cultures using siRNA knockdown. Consistent with its previously identified role in synaptic gene expression, loss of ZCCHC17 led to loss of synaptic protein expression. Patch recording of neurons shows that ZCCHC17 loss significantly disrupted the excitation/inhibition balance of neurotransmission, and favored excitatory-dominant synaptic activity as measured by an increase in spontaneous excitatory post synaptic currents and action potential firing rate, and a decrease in spontaneous inhibitory post synaptic currents. These findings are consistent with the hyperexcitable phenotype seen in AD animal models and in patients. We are the first to assess the functional consequences of ZCCHC17 knockdown in neurons and conclude that ZCCHC17 loss partially phenocopies AD-related loss of synaptic proteins and hyperexcitability.

Spatial and temporal pattern of structure-function coupling of human brain connectome with development.

Brain structural circuitry shapes a richly patterned functional synchronization, supporting for complex cognitive and behavioural abilities. However, how coupling of structural connectome (SC) and functional connectome (FC) develops and its relationships with cognitive functions and transcriptomic architecture remain unclear. We used multimodal magnetic resonance imaging data from 439 participants aged 5.7-21.9 years to predict functional connectivity by incorporating intracortical and extracortical structural connectivity, characterizing SC-FC coupling. Our findings revealed that SC-FC coupling was strongest in the visual and somatomotor networks, consistent with evolutionary expansion, myelin content, and functional principal gradient. As development progressed, SC-FC coupling exhibited heterogeneous alterations dominated by an increase in cortical regions, broadly distributed across the somatomotor, frontoparietal, dorsal attention, and default mode networks. Moreover, we discovered that SC-FC coupling significantly predicted individual variability in general intelligence, mainly influencing frontoparietal and default mode networks. Finally, our results demonstrated that the heterogeneous development of SC-FC coupling is positively associated with genes in oligodendrocyte-related pathways and negatively associated with astrocyte-related genes. This study offers insight into the maturational principles of SC-FC coupling in typical development.

The effect of sucrose consumption on eating behavior and depression during morphine withdrawal period in rats

BACKGROUND: Sugary drink and junk food consumption increases during the withdrawal period, leading to subsequent psychological and metabolic alterations. OBJECTIVES: We aimed to investigate the relationship of sucrose consumption with serum insulin levels, leptin levels, brain Dopamine-2 receptor (D2R) expression, food consumption, and anxiety-depression findings in morphine-withdrawal rats. METHODS: Thirty-six male Wistar albino rats were divided into six groups: Control, sucrose-free, 5% sucrose, 10% sucrose, 20% sucrose, and an addiction test. Saline was intraperitoneally injected to the control group, and morphine was intraperitoneally injected to the other groups for 14 days. After 14 days, naloxone was administered to the addiction test group, and addiction symptoms were observed and this group was sacrificed on the same day. Other groups were fed ad libitum with different concentrations of sucrose solution for one week. Behavioral parameters were evaluated at the end of the experiment. Leptin and insulin concentrations in serum and D2R levels in brain tissues were detected using an enzyme-linked immunosorbent assay. D2R concentrations in brain tissues were evaluated utilizing immunohistochemistry. RESULTS: We observed decreased food consumption and increased fluid consumption in rats that consumed sucrose water during the withdrawal period. The level of depression and binge eating behavior was elevated in groups consuming sucrose, and the 10% sucrose group had the highest carbohydrate consumption and anxiety levels. In addition, the 10% sucrose group had the lowest brain D2R expression. The leptin level was highest in the 20% sucrose group. CONCLUSIONS: These results show the possible effects of sugary drinks consumed during the withdrawal period.

Effects of Fetal Position on the Loading of the Fetal Brain During the Onset of the Second Stage of Labor.

During vaginal delivery, the delivery requires the fetal head to mold to accommodate the geometric constraints of the birth canal. Excessive molding can produce brain injuries and long-term sequelae. Understanding the loading of the fetal brain during the second stage of labor (fully dilated cervix, active pushing, and expulsion of fetus) could thus help predict the safety of the newborn during vaginal delivery. To this end, this study proposes a finite element model of the fetal head and maternal canal environment that is capable of predicting the stresses experienced by the fetal brain at the onset of the second phase of labor. Both fetal and maternal models were adapted from existing studies to represent the geometry of full-term pregnancy. Two fetal positions were compared: left-occiput-anterior and left-occiput-posterior. The results demonstrate that left-occiput-anterior position reduces the maternal tissue deformation, at the cost of higher stress in the fetal brain. In both cases, stress is concentrated underneath the sutures, though the location varies depending on the presentation. In summary, this study provides a patient-specific simulation platform for the study of vaginal delivery and its effect on both the fetal brain and maternal anatomy. Finally, it is suggested that such an approach has the potential to be used by obstetricians to support their decision-making processes through the simulation of various delivery scenarios.

Perceptual Awareness in Human Infants: What is the Evidence?

Perceptual awareness in infants during the first year of life is understudied, despite the philosophical, scientific, and clinical importance of understanding how and when consciousness emerges during human brain development. Although parents are undoubtedly convinced that their infant is conscious, the lack of adequate experimental paradigms to address this question in preverbal infants has been a hindrance to research on this topic. However, recent behavioral and brain imaging studies have shown that infants are engaged in complex learning from an early age and that their brains are more structured than traditionally thought. I will present a rapid overview of these results, which might provide indirect evidence of early perceptual awareness and then describe how a more systematic approach to this question could stand within the framework of global workspace theory, which identifies specific signatures of conscious perception in adults. Relying on these brain signatures as a benchmark for conscious perception, we can deduce that it exists in the second half of the first year, whereas the evidence before the age of 5 months is less solid, mainly because of the paucity of studies. The question of conscious perception before term remains open, with the possibility of short periods of conscious perception, which would facilitate early learning. Advances in brain imaging and growing interest in this subject should enable us to gain a better understanding of this important issue in the years to come.

Comparative Analysis of Human-Chimpanzee Divergence in Brain Connectivity and its Genetic Correlates.

Chimpanzees (Pan troglodytes) are humans' closest living relatives, making them the most directly relevant comparison point for understanding human brain evolution. Zeroing in on the differences in brain connectivity between humans and chimpanzees can provide key insights into the specific evolutionary changes that might have occured along the human lineage. However, conducting comparisons of brain connectivity between humans and chimpanzees remains challenging, as cross-species brain atlases established within the same framework are currently lacking. Without the availability of cross-species brain atlases, the region-wise connectivity patterns between humans and chimpanzees cannot be directly compared. To address this gap, we built the first Chimpanzee Brainnetome Atlas (ChimpBNA) by following a well-established connectivity-based parcellation framework. Leveraging this new resource, we found substantial divergence in connectivity patterns across most association cortices, notably in the lateral temporal and dorsolateral prefrontal cortex between the two species. Intriguingly, these patterns significantly deviate from the patterns of cortical expansion observed in humans compared to chimpanzees. Additionally, we identified regions displaying connectional asymmetries that differed between species, likely resulting from evolutionary divergence. Genes associated with these divergent connectivities were found to be enriched in cell types crucial for cortical projection circuits and synapse formation. These genes exhibited more pronounced differences in expression patterns in regions with higher connectivity divergence, suggesting a potential foundation for brain connectivity evolution. Therefore, our study not only provides a fine-scale brain atlas of chimpanzees but also highlights the connectivity divergence between humans and chimpanzees in a more rigorous and comparative manner and suggests potential genetic correlates for the observed divergence in brain connectivity patterns between the two species. This can help us better understand the origins and development of uniquely human cognitive capabilities.

Early life exposure to queen mandibular pheromone mediates persistent transcriptional changes in the brain of honey bee foragers.

Behavioural regulation in insect societies remains a fundamental question in sociobiology. In hymenopteran societies, the queen plays a crucial role in regulating group behaviour by affecting individual behaviour and physiology through modulation of worker gene expression. Honey bee (Apis mellifera) queens signal their presence via queen mandibular pheromone (QMP). While QMP has been shown to influence behaviour and gene expression of young workers, we know little about how these changes translate in older workers. The effects of the queen pheromone could have prolonged molecular impacts on workers that depend on an early sensitive period. We demonstrate that removal of QMP impacts long-term gene expression in the brain and antennae in foragers that were treated early in life (1day post emergence), but not when treated later in life. Genes important for division of labour, learning, chemosensory perception and ageing were among those differentially expressed in the antennae and brain tissues, suggesting that QMP influences diverse physiological and behavioural processes in workers. Surprisingly, removal of QMP did not have an impact on foraging behaviour. Overall, our study suggests a sensitive period early in the life of workers, where the presence or absence of a queen has potentially life-long effects on transcriptional activity.

Distance and grid-like codes support the navigation of abstract social space in the human brain.

People form impressions about others during daily social encounters and infer personality traits from others' behaviors. Such trait inference is thought to rely on two universal dimensions: competence and warmth. These two dimensions can be used to construct a 'social cognitive map' organizing massive information obtained from social encounters efficiently. Originating from spatial cognition, the neural codes supporting the representation and navigation of spatial cognitive maps have been widely studied. Recent studies suggest similar neural mechanism subserves the map-like architecture in social cognition as well. Here we investigated how spatial codes operate beyond the physical environment and support the representation and navigation of social cognitive map. We designed a social value space defined by two dimensions of competence and warmth. Behaviorally, participants were able to navigate to a learned location from random starting locations in this abstract social space. At the neural level, we identified the representation of distance in the precuneus, fusiform gyrus, and middle occipital gyrus. We also found partial evidence of grid-like representation patterns in the medial prefrontal cortex and entorhinal cortex. Moreover, the intensity of grid-like response scaled with the performance of navigating in social space and social avoidance trait scores. Our findings suggest a neurocognitive mechanism by which social information can be organized into a structured representation, namely cognitive map and its relevance to social well-being.

Dynamic representation of multidimensional object properties in the human brain.

Our visual world consists of an immense number of unique objects and yet, we are easily able to identify, distinguish, interact, and reason about the things we see within a few hundred milliseconds. This requires that we integrate and focus on a wide array of object properties to support specific behavioral goals. In the current study, we examined how these rich object representations unfold in the human brain by modelling time-resolved MEG signals evoked by viewing single presentations of tens of thousands of object images. Based on millions of behavioral judgments, the object space can be captured in 66 dimensions that we use to guide our understanding of the neural representation of this space. We find that all dimensions are reflected in the time course of response with distinct temporal profiles for different object dimensions. These profiles fell into two broad types, with either a distinct and early peak (∼125 ms) or a slow rise to a late peak (∼300 ms). Further, early effects were stable across participants, in contrast to later effects which showed more variability, suggesting that early peaks may carry stimulus-specific and later peaks more participant-specific information. Dimensions with early peaks appeared to be primarily visual dimensions and those with later peaks more conceptual, suggesting that conceptual representations are more variable across people. Together, these data provide a comprehensive account of how behaviorally-relevant object properties unfold in the human brain and contribute to the rich nature of object vision.

Blind Quality Assessment of Dense 3D Point Clouds with Structure Guided Resampling

Objective quality assessment of three-dimensional (3D) point clouds is essential for the development of immersive multimedia systems in real-world applications. Despite the success of perceptual quality evaluation for 2D images and videos, blind/no-reference metrics are still scarce for 3D point clouds with large-scale irregularly distributed 3D points. Therefore, in this article, we propose an objective point cloud quality index with Structure Guided Resampling (SGR) to automatically evaluate the perceptually visual quality of dense 3D point clouds. The proposed SGR is a general-purpose blind quality assessment method without the assistance of any reference information. Specifically, considering that the human visual system is highly sensitive to structure information, we first exploit the unique normal vectors of point clouds to execute regional pre-processing that consists of keypoint resampling and local region construction. Then, we extract three groups of quality-related features, including (1) geometry density features, (2) color naturalness features, and (3) angular consistency features. Both the cognitive peculiarities of the human brain and naturalness regularity are involved in the designed quality-aware features that can capture the most vital aspects of distorted 3D point clouds. Extensive experiments on several publicly available subjective point cloud quality databases validate that our proposed SGR can compete with state-of-the-art full-reference, reduced-reference, and no-reference quality assessment algorithms.

Parallel Multilink Group Joint ICA: Fusion of 3D Structural and 4D Functional Data Across Multiple Resting fMRI Networks.

Multimodal neuroimaging research plays a pivotal role in understanding the complexities of the human brain and its disorders. Independent component analysis (ICA) has emerged as a widely used and powerful tool for disentangling mixed independent sources, particularly in the analysis of functional magnetic resonance imaging (fMRI) data. This paper extends the use of ICA as a unifying framework for multimodal fusion, introducing a novel approach termed parallel multilink group joint ICA (pmg-jICA). The method allows for the fusion of gray matter maps from structural MRI (sMRI) data to multiple fMRI intrinsic networks, addressing the limitations of previous models. The effectiveness of pmg-jICA is demonstrated through its application to an Alzheimer's dataset, yielding linked structure-function outputs for 53 brain networks. Our approach leverages the complementary information from various imaging modalities, providing a unique perspective on brain alterations in Alzheimer's disease. The pmg-jICA identifies several components with significant differences between HC and AD groups including thalamus, caudate, putamen with in the subcortical (SC) domain, insula, parahippocampal gyrus within the cognitive control (CC) domain, and the lingual gyrus within the visual (VS) domain, providing localized insights into the links between AD and specific brain regions. In addition, because we link across multiple brain networks, we can also compute functional network connectivity (FNC) from spatial maps and subject loadings, providing a detailed exploration of the relationships between different brain regions and allowing us to visualize spatial patterns and loading parameters in sMRI along with intrinsic networks and FNC from the fMRI data. In essence, developed approach combines concepts from joint ICA and group ICA to provide a rich set of output characterizing data-driven links between covarying gray matter networks, and a (potentially large number of) resting fMRI networks allowing further study in the context of structure/function links. We demonstrate the utility of the approach by highlighting key structure/function disruptions in Alzheimer's individuals.

7,8-Dihydroxyflavone is a direct inhibitor of human and murine pyridoxal phosphatase.

Vitamin B6 deficiency has been linked to cognitive impairment in human brain disorders for decades. Still, the molecular mechanisms linking vitamin B6 to these pathologies remain poorly understood, and whether vitamin B6 supplementation improves cognition is unclear as well. Pyridoxal 5'-phosphate phosphatase (PDXP), an enzyme that controls levels of pyridoxal 5'-phosphate (PLP), the co-enzymatically active form of vitamin B6, may represent an alternative therapeutic entry point into vitamin B6-associated pathologies. However, pharmacological PDXP inhibitors to test this concept are lacking. We now identify a PDXP and age-dependent decline of PLP levels in the murine hippocampus that provides a rationale for the development of PDXP inhibitors. Using a combination of small-molecule screening, protein crystallography, and biolayer interferometry, we discover, visualize, and analyze 7,8-dihydroxyflavone (7,8-DHF) as a direct and potent PDXP inhibitor. 7,8-DHF binds and reversibly inhibits PDXP with low micromolar affinity and sub-micromolar potency. In mouse hippocampal neurons, 7,8-DHF increases PLP in a PDXP-dependent manner. These findings validate PDXP as a druggable target. Of note, 7,8-DHF is a well-studied molecule in brain disorder models, although its mechanism of action is actively debated. Our discovery of 7,8-DHF as a PDXP inhibitor offers novel mechanistic insights into the controversy surrounding 7,8-DHF-mediated effects in the brain.

Task structure tailors the geometry of neural representations in human lateral prefrontal cortex.

How do human brains represent tasks of varying structure? The lateral prefrontal cortex (lPFC) flexibly represents task information. However, principles that shape lPFC representational geometry remain unsettled. We use deep sampling fMRI and pattern analyses to reveal the detailed structure of lPFC representational geometries as humans perform two distinct categorization tasks, one with flat, conjunctive categories and another with hierarchical, context-dependent categories. We show that lPFC encodes task relevant information with task tailored geometries of intermediate dimensionality. These geometries preferentially enhance the separability of task relevant variables while encoding a subset in abstract form. Specifically, in the flat task, a global axis encodes response relevant categories abstractly, while category- specific local geometries are high dimensional. In the hierarchy task, a global axis abstractly encodes the higher level context, while low dimensional, context- specific local geometries compress irrelevant information and abstractly encode the relevant information. Comparing these task geometries exposes generalizable principles by which lPFC tailors representations to different tasks.

Functional connectome through the human life span.

The lifespan growth of the functional connectome remains unknown. Here, we assemble task-free functional and structural magnetic resonance imaging data from 33,250 individuals aged 32 postmenstrual weeks to 80 years from 132 global sites. We report critical inflection points in the nonlinear growth curves of the global mean and variance of the connectome, peaking in the late fourth and late third decades of life, respectively. After constructing a fine-grained, lifespan-wide suite of system-level brain atlases, we show distinct maturation timelines for functional segregation within different systems. Lifespan growth of regional connectivity is organized along a primary-to-association cortical axis. These connectome-based normative models reveal substantial individual heterogeneities in functional brain networks in patients with autism spectrum disorder, major depressive disorder, and Alzheimer's disease. These findings elucidate the lifespan evolution of the functional connectome and can serve as a normative reference for quantifying individual variation in development, aging, and neuropsychiatric disorders.