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The ventral visual stream is organized into units, or functional regions of interest (fROIs), specialized for processing high-level visual categories. Task-based fMRI scans ("localizers") are typically used to identify each individual's nuanced set of fROIs. The unique landscape of an individual's functional activation may rely in large part on their specialized connectivity patterns; recent studies corroborate this by showing that connectivity can predict individual differences in neural responses. We focus on the ventral visual stream and ask: how well can an individual's resting state functional connectivity localize their fROIs for face, body, scene, and object perception? And are the neural processors for any particular visual category better predicted by connectivity than others, suggesting a tighter mechanistic relationship between connectivity and function? We found, among 18 fROIs predicted from connectivity for each subject, all but one were selective for their preferred visual category. Defining an individual's fROIs based on their connectivity patterns yielded regions that were more selective than regions identified from previous studies or atlases in nearly all cases. Overall, we found that in the absence of a domain-specific localizer task, a 10-min resting state scan can be reliably used for defining these fROIs., (© 2024. The Author(s).)

Introduction: Convergence insufficiency (CI) is an oculomotor abnormality characterised by exophoria and inadequate convergence when focusing on nearby objects. CI has been shown to cause symptoms when reading. However, the downstream consequences on brain structure have yet to be investigated. Here, we investigated the neural consequences of symptomatic CI, focusing on the left arcuate fasciculus, a bundle of white matter fibres which supports reading ability and has been associated with reading deficits., Methods: We compared the arcuate fasciculus microstructure of participants with symptomatic CI versus normal binocular vision (NBV). Six CI participants and seven NBV controls were included in the analysis. All participants were scanned with 3 T magnetic resonance imaging (MRI), and anatomical and diffusion-weighted images were acquired. Diffusion-weighted images were processed with TRACULA to identify the arcuate fasciculus in each participant and compute volume and radial diffusivity (RD)., Results: Compared with NBV controls, those with symptomatic CI had significantly smaller arcuate fasciculi bilaterally (left: t = -3.21, p = 0.008; right: t = -3.29, p = 0.007), and lower RD in the left (t = -2.66, p = 0.02), but not the right (t = -0.81, p = 0.44, false discovery rate (FDR)-corrected p > 0.05) arcuate fasciculus. Those with higher levels of reading symptoms had smaller arcuate fasciculi (r = -0.74, p = 0.004) with lower RD (r = -0.61, p = 0.03)., Conclusions: These findings suggest that symptomatic CI may lead to microstructural changes in the arcuate fasciculus. Since it is highly unlikely that abnormalities in the arcuate fasciculus are the cause of the neuromuscular deficits in the eyes, we argue that these changes may be a potential neuroplastic consequence of disruptions in sustained reading., (© 2024 The Authors. Ophthalmic and Physiological Optics published by John Wiley & Sons Ltd on behalf of College of Optometrists.)

Advances in functional MRI (fMRI) allow mapping an individual's brain function in vivo. Task fMRI can localize domain-specific regions of cognitive processing or functional regions of interest (fROIs) within an individual. Moreover, data from resting state (no task) fMRI can be used to define an individual's connectome, which can characterize that individual's functional organization via connectivity-based parcellations. However, can connectivity-based parcellations alone predict an individual's fROIs? Here, we describe an approach to compute individualized rs-fROIs (i.e., regions that correspond to given fROI constructed using only resting state data) for motor control, working memory, high-level vision, and language comprehension. The rs-fROIs were computed and validated using a large sample of young adults ( n = 1,018) with resting state and task fMRI from the Human Connectome Project. First, resting state parcellations were defined across a sequence of resolutions from broadscale to fine-grained networks in a training group of 500 individuals. Second, 21 rs-fROIs were defined from the training group by identifying the rs network that most closely matched task-defined fROIs across all individuals. Third, the selectivity of rs-fROIs was investigated in a training set of the remaining 518 individuals. All computed rs-fROIs were indeed selective for their preferred category. Critically, the rs-fROIs had higher selectivity than probabilistic atlas parcels for nearly all fROIs. In conclusion, we present a potential approach to define selective fROIs on an individual-level circumventing the need for multiple task-based localizers. NEW & NOTEWORTHY We compute individualized resting state parcels that identify an individual's own functional regions of interest (fROIs) for high-level vision, language comprehension, motor control, and working memory, using only their functional connectome. This approach demonstrates a rapid and powerful alternative for finding a large set of fROIs in an individual, using only their unique connectivity pattern, which does not require the costly acquisition of multiple fMRI localizer tasks.

Introduction: Extremely preterm (EPT) birth, defined as birth at a gestational age (GA) <28 weeks, can have a lasting impact on cognition throughout the life span. Previous investigations reveal differences in brain structure and connectivity between infants born preterm and full-term (FT), but how does preterm birth impact the adolescent connectome? Methods: In this study, we investigate how EPT birth can alter broadscale network organization later in life by comparing resting-state functional magnetic resonance imaging connectome-based parcellations of the entire cortex in adolescents born EPT ( N  = 22) to age-matched adolescents born FT (GA ≥37 weeks, N  = 28). We compare these parcellations to adult parcellations from previous studies and explore the relationship between an individual's network organization and behavior. Results: Primary (occipital and sensorimotor) and frontoparietal networks were observed in both groups. However, there existed notable differences in the limbic and insular networks. Surprisingly, the connectivity profile of the limbic network of EPT adolescents was more adultlike than the same network in FT adolescents. Finally, we found a relationship between adolescents' overall cognition score and their limbic network maturity. Discussion: Overall, preterm birth may contribute to the atypical development of broadscale network organization in adolescence and may partially explain the observed cognitive deficits.

Many adults cannot voluntarily recall memories before the ages of 3-5, a phenomenon referred to as "infantile amnesia." The development of the hippocampal network likely plays a significant part in the emergence of the ability to form long-lasting memories. In adults, the hippocampus has specialized and privileged connections with certain cortical networks, which presumably facilitate its involvement in memory encoding, consolidation, and retrieval. Is the hippocampus already specialized in these cortical connections at birth? And are the topographical principles of connectivity (e.g., long-axis specialization) present at birth? We analyzed resting-state hippocampal connectivity in neonates scanned within 1 wk of birth (Developmental Human Connectome Project) and compared it with that of adults (Human Connectome Project). We explored the connections of the whole hippocampus and its long-axis specialization to seven canonical cortical networks. We found that the neonatal hippocampal networks show clear immaturity at birth: adults showed hippocampal connectivity that was unique for each cortical network, whereas neonates showed no differentiation in hippocampal connectivity across these networks. Furthermore, neonates lacked long-axis specialization (i.e., along the anterior-posterior axis) of the hippocampus in its differential connectivity patterns to the cortical networks. This immaturity in connectivity may contribute to immaturity in memory formation in the first years of life. NEW & NOTEWORTHY Although both animal data and human data suggest that the hippocampus is immature at birth, to date, there are no direct assessments of human hippocampal functional connectivity (FC) very early in life. Our study explores the FC of the hippocampus to the cortex at birth, allowing insight into the development of human memory systems. In particular, we find that adults and neonates exhibit vastly different hippocampal connectivity profiles-a finding that likely has large developmental implications.

What determines the functional organization of cortex? One hypothesis is that innate connectivity patterns, either structural or functional connectivity, set up a scaffold upon which functional specialization can later take place. We tested this hypothesis by asking whether the visual word form area (VWFA), an experience-driven region, was already functionally connected to proto language networks in neonates scanned within one week of birth. Using the data from the Human Connectone Project (HCP) and the Developing Human Connectome Project (dHCP), we calculated intrinsic functional connectivity during resting-state functional magnetic resonance imaging (fMRI), and found that neonates showed similar functional connectivity patterns to adults. We observed that (1) language regions connected more strongly with the putative VWFA than other adjacent ventral visual regions that also show foveal bias, and (2) the VWFA connected more strongly with frontotemporal language regions than with regions adjacent to these language regions. These data suggest that the location of the VWFA is earmarked at birth due to its connectivity with the language network, providing evidence that innate connectivity instructs the later refinement of cortex.

The cortical dorsal attention network (DAN) is a set of parietal and frontal regions that support a wide variety of attentionally demanding tasks. Whereas attentional deployment reliably drives DAN activity across subjects, there is a large degree of variation in the activation pattern in individual subjects. We hypothesize that a subject's own idiosyncratic pattern of cortical DAN activity can be predicted from that subject's own unique pattern of functional connectivity. By modeling task activation as a function of whole brain connectivity patterns, we are able to define the connectivity fingerprints for the frontal and parietal DAN, and use it to predict a subject's characteristic DAN activation pattern with high accuracy. These predictions outperform the standard group-average benchmark and predict a subject's own activation pattern above and beyond predictions from another subject's connectivity pattern. Thus an individual's distinctive connectivity pattern accounts for substantial variance in DAN functional responses. Last, we show that the set of connections that predict cortical DAN responses, the frontal and parietal DAN connectivity fingerprints, is predominantly composed of other coactive regions, including regions outside of the DAN including occipital and temporal visual cortices. These connectivity fingerprints represent defining computational characteristics of the DAN, delineating which voxels are or are not capable of exerting top-down attentional bias to other regions of the brain. NEW & NOTEWORTHY The dorsal attention network (DAN) is a set of regions in frontoparietal cortex that reliably activate during attentional tasks. We designed computational models that predict the degree of an individual's DAN activation using their resting-state connectivity pattern alone. This uncovered the connectivity fingerprints of the DAN, which define it so well that we can predict how a voxel will respond to an attentional task given only its pattern of connectivity, with outstanding accuracy.

The human cerebral cortex is estimated to comprise 200-300 distinct functional regions per hemisphere. Identification of the precise anatomical location of an individual's unique set of functional regions is a challenge for neuroscience that has broad scientific and clinical utility. Recent studies have demonstrated the existence of four interleaved regions in lateral frontal cortex (LFC) that are part of broader visual attention and auditory attention networks (Michalka et al., 2015; Noyce et al., 2017; Tobyne et al., 2017). Due to a large degree of inter-subject anatomical variability, identification of these regions depends critically on within-subject analyses. Here, we demonstrate that, for both sexes, an individual's unique pattern of resting-state functional connectivity can accurately identify their specific pattern of visual- and auditory-selective working memory and attention task activation in lateral frontal cortex (LFC) using "connectome fingerprinting." Building on prior techniques (Saygin et al., 2011; Osher et al., 2016; Tavor et al., 2016; Smittenaar et al., 2017; Wang et al., 2017; Parker Jones et al., 2017), we demonstrate here that connectome fingerprint predictions are far more accurate than group-average predictions and match the accuracy of within-subject task-based functional localization, while requiring less data. These findings are robust across brain parcellations and are improved with penalized regression methods. Because resting-state data can be easily and rapidly collected, these results have broad implications for both clinical and research investigations of frontal lobe function. Our findings also provide a set of recommendations for future research., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Substantial portions of the cerebellum appear to support non-motor functions; however, previous investigations of cerebellar involvement in cognition have revealed only a coarse degree of specificity. Although somatotopic maps have been observed within cerebellum, similar precision within cortico-cerebellar networks supporting non-motor functions has not previously been reported. Here, we find that human cerebellar lobule VIIb/VIIIa differentially codes key aspects of visuospatial cognition. Ipsilateral visuospatial representations were observed during both a visual working memory and an attentionally demanding visual receptive field-mapping fMRI task paradigm. Moreover, within lobule VIIb/VIIIa, we observed a functional dissociation between spatial coding and visual working memory processing. Visuospatial representations were found in the dorsomedial portion of lobule VIIb/VIIIa, and load-dependent visual working memory processing was shifted ventrolaterally. A similar functional gradient for spatial versus load processing was found in posterior parietal cortex. This cerebral cortical organization was well predicted by functional connectivity with spatial and load regions of cerebellar lobule VIIb/VIIIa. Collectively, our findings indicate that recruitment by visuospatial attentional functions within cerebellar lobule VIIb/VIIIa is highly specific. Furthermore, the topographic arrangement of these functions is mirrored in frontal and parietal cortex. These findings motivate a closer examination of cortico-cerebellar functional specialization across a broad range of cognitive domains., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Human frontal cortex is commonly described as being insensitive to sensory modality, however several recent studies cast doubt on this view. Our laboratory previously reported two visual-biased attention regions interleaved with two auditory-biased attention regions, bilaterally, within lateral frontal cortex. These regions selectively formed functional networks with posterior visual-biased and auditory-biased attention regions. Here, we conducted a series of functional connectivity analyses to validate and expand this analysis to 469 subjects from the Human Connectome Project (HCP). Functional connectivity analyses replicated the original findings and revealed a novel hemispheric connectivity bias. We also subdivided lateral frontal cortex into 21 thin-slice ROIs and observed bilateral patterns of spatially alternating visual-biased and auditory-biased attention network connectivity. Finally, we performed a correlation difference analysis that revealed five additional bilateral lateral frontal regions differentially connected to either the visual-biased or auditory-biased attention networks. These findings leverage the HCP dataset to demonstrate that sensory-biased attention networks may have widespread influence in lateral frontal cortical organization., (Copyright © 2017 Elsevier Inc. All rights reserved.)

What determines the cortical location at which a given functionally specific region will arise in development? We tested the hypothesis that functionally specific regions develop in their characteristic locations because of pre-existing differences in the extrinsic connectivity of that region to the rest of the brain. We exploited the visual word form area (VWFA) as a test case, scanning children with diffusion and functional imaging at age 5, before they learned to read, and at age 8, after they learned to read. We found the VWFA developed functionally in this interval and that its location in a particular child at age 8 could be predicted from that child's connectivity fingerprints (but not functional responses) at age 5. These results suggest that early connectivity instructs the functional development of the VWFA, possibly reflecting a general mechanism of cortical development.

Unlabelled: The "dorsal attention network" or "frontoparietal network" refers to a network of cortical regions that support sustained attention and working memory. Recent work has demonstrated that cortical nodes of the dorsal attention network possess intrinsic functional connections with a region in ventral cerebellum, in the vicinity of lobules VII/VIII. Here, we performed a series of task-based and resting-state fMRI experiments to investigate cerebellar participation in the dorsal attention network in humans. We observed that visual working memory and visual attention tasks robustly recruit cerebellar lobules VIIb and VIIIa, in addition to canonical cortical dorsal attention network regions. Across the cerebellum, resting-state functional connectivity with the cortical dorsal attention network strongly predicted the level of activation produced by attention and working memory tasks. Critically, cerebellar voxels that were most strongly connected with the dorsal attention network selectively exhibited load-dependent activity, a hallmark of the neural structures that support visual working memory. Finally, we examined intrinsic functional connectivity between task-responsive portions of cerebellar lobules VIIb/VIIIa and cortex. Cerebellum-to-cortex functional connectivity strongly predicted the pattern of cortical activation during task performance. Moreover, resting-state connectivity patterns revealed that cerebellar lobules VIIb/VIIIa group with cortical nodes of the dorsal attention network. This evidence leads us to conclude that the conceptualization of the dorsal attention network should be expanded to include cerebellar lobules VIIb/VIIIa., Significance Statement: The functional participation of cerebellar structures in nonmotor cortical networks remains poorly understood and is highly understudied, despite the fact that the cerebellum possesses many more neurons than the cerebral cortex. Although visual attention paradigms have been reported to activate cerebellum, many researchers have largely dismissed the possibility of a cerebellar contribution to attention in favor of a motor explanation, namely, eye movements. The present study demonstrates that a cerebellar subdivision (mainly lobules VIIb/VIIIa), which exhibits strong intrinsic functional connectivity with the cortical dorsal attention network, also closely mirrors a myriad of cortical dorsal attention network responses to visual attention and working memory tasks. This evidence strongly supports a reconceptualization of the dorsal attention network to include cerebellar lobules VIIb/VIIIa., (Copyright © 2016 the authors 0270-6474/16/366083-14$15.00/0.)

A fundamental and largely unanswered question in neuroscience is whether extrinsic connectivity and function are closely related at a fine spatial grain across the human brain. Using a novel approach, we found that the anatomical connectivity of individual gray-matter voxels (determined via diffusion-weighted imaging) alone can predict functional magnetic resonance imaging (fMRI) responses to 4 visual categories (faces, objects, scenes, and bodies) in individual subjects, thus accounting for both functional differentiation across the cortex and individual variation therein. Furthermore, this approach identified the particular anatomical links between voxels that most strongly predict, and therefore plausibly define, the neural networks underlying specific functions. These results provide the strongest evidence to date for a precise and fine-grained relationship between connectivity and function in the human brain, raise the possibility that early-developing connectivity patterns may determine later functional organization, and offer a method for predicting fine-grained functional organization in populations who cannot be functionally scanned., (© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

A large corpus of research suggests that there are changes in the manner and degree to which the amygdala supports cognitive and emotional function across development. One possible basis for these developmental differences could be the maturation of amygdalar connections with the rest of the brain. Recent functional connectivity studies support this conclusion, but the structural connectivity of the developing amygdala and its different nuclei remains largely unstudied. We examined age related changes in the DWI connectivity fingerprints of the amygdala to the rest of the brain in 166 individuals of ages 5-30. We also developed a model to predict age based on individual-subject amygdala connectivity, and identified the connections that were most predictive of age. Finally, we segmented the amygdala into its four main nucleus groups, and examined the developmental changes in connectivity for each nucleus. We observed that with age, amygdalar connectivity becomes increasingly sparse and localized. Age related changes were largely localized to the subregions of the amygdala that are implicated in social inference and contextual memory (the basal and lateral nuclei). The central nucleus' connectivity also showed differences with age but these differences affected fewer target regions than the basal and lateral nuclei. The medial nucleus did not exhibit any age related changes. These findings demonstrate increasing specificity in the connectivity patterns of amygdalar nuclei across age.

Developmental dyslexia, an unexplained difficulty in learning to read, has been associated with alterations in white matter organization as measured by diffusion-weighted imaging. It is unknown, however, whether these differences in structural connectivity are related to the cause of dyslexia or if they are consequences of reading difficulty (e.g., less reading experience or compensatory brain organization). Here, in 40 kindergartners who had received little or no reading instruction, we examined the relation between behavioral predictors of dyslexia and white matter organization in left arcuate fasciculus, inferior longitudinal fasciculus, and the parietal portion of the superior longitudinal fasciculus using probabilistic tractography. Higher composite phonological awareness scores were significantly and positively correlated with the volume of the arcuate fasciculus, but not with other tracts. Two other behavioral predictors of dyslexia, rapid naming and letter knowledge, did not correlate with volumes or diffusion values in these tracts. The volume and fractional anisotropy of the left arcuate showed a particularly strong positive correlation with a phoneme blending test. Whole-brain regressions of behavioral scores with diffusion measures confirmed the unique relation between phonological awareness and the left arcuate. These findings indicate that the left arcuate fasciculus, which connects anterior and posterior language regions of the human brain and which has been previously associated with reading ability in older individuals, is already smaller and has less integrity in kindergartners who are at risk for dyslexia because of poor phonological awareness. These findings suggest a structural basis of behavioral risk for dyslexia that predates reading instruction.

A fundamental assumption in neuroscience is that brain structure determines function. Accordingly, functionally distinct regions of cortex should be structurally distinct in their connections to other areas. We tested this hypothesis in relation to face selectivity in the fusiform gyrus. By using only structural connectivity, as measured through diffusion-weighted imaging, we were able to predict functional activation to faces in the fusiform gyrus. These predictions outperformed two control models and a standard group-average benchmark. The structure-function relationship discovered from the initial participants was highly robust in predicting activation in a second group of participants, despite differences in acquisition parameters and stimuli. This approach can thus reliably estimate activation in participants who cannot perform functional imaging tasks and is an alternative to group-activation maps. Additionally, we identified cortical regions whose connectivity was highly influential in predicting face selectivity within the fusiform, suggesting a possible mechanistic architecture underlying face processing in humans.

The amygdala plays an important role in emotional and social functions, and amygdala dysfunction has been associated with multiple neuropsychiatric disorders, including autism, anxiety, and depression. Although the amygdala is composed of multiple anatomically and functionally distinct nuclei, typical structural magnetic resonance imaging (MRI) sequences are unable to discern them. Thus, functional MRI (fMRI) studies typically average the BOLD response over the entire structure, which reveals some aspects of amygdala function as a whole but does not distinguish the separate roles of specific nuclei in humans. We developed a method to segment the human amygdala into its four major nuclei using only diffusion-weighted imaging and connectivity patterns derived mainly from animal studies. We refer to this new method as Tractography-based Segmentation, or TractSeg. The segmentations derived from TractSeg were topographically similar to their corresponding amygdaloid nuclei, and were validated against a high-resolution scan in which the nucleic boundaries were visible. In addition, nuclei topography was consistent across subjects. TractSeg relies on short scan acquisitions and widely accessible software packages, making it attractive for use in healthy populations to explore normal amygdala nucleus function, as well as in clinical and pediatric populations. Finally, it paves the way for implementing this method in other anatomical regions which are also composed of functional subunits that are difficult to distinguish with standard structural MRI., (Copyright © 2011 Elsevier Inc. All rights reserved.)