Biology subjects

Dosenbach, N. U. F.

Publications and source records attributed to Dosenbach, N. U. F..

At least 19 recordsLinked to original sources

bioRxiv2026

Movie Watching for Individual Functional Brain Network Estimation in Adolescents

Precision functional mapping (PFM) reveals stable individual differences in brain functional network organization and holds promise for advancing neuropsychiatric clinical care. PFM requires sufficient high-quality and densely-sampled functional MRI data at the individual level that is typically acquired during the so-called resting state while passively fixating on a crosshair. However, crosshair fixation acquisitions can be challenging especially for pediatric or patient populations, where alternatives like movie watching might be used to improve data quality and reduce participant burden. Here, we compare the use of resting state crosshair fixation and movie watching fMRI data to derive individual-specific functional brain network topography using PFM data (28-38 minutes of low-motion fMRI data per-participant per-condition) in nineteen adolescents (12-18 years) with a range of transdiagnostic psychiatric diagnoses. Network assignments were largely conserved between crosshair fixation and movie watching, with a smaller subset of reproducible network reassignments which were overwhelmingly border shifts between neighboring networks. This suggests largely conserved global structure of functional network topography between crosshair fixation and movie watching, though border shifts can compound into variable estimates of cortical network size particularly for movie positive (language, salience, and parietal memory) and movie negative networks (default mode, action mode). Functional network assignments derived from movies and crosshair were also similarly individual-specific and consistent within common neuromodulation targets including dorsolateral prefrontal cortex and somatomotor cortex. Key results were replicated in independent pediatric consortia data (Healthy Brain Network, n = 466, 6-22 years) and reproduced across independent PFM data sessions. Acknowledging individual differences and level of analysis, we conclude that movies are a viable alternative to resting state crosshair fixation for individual network definitions.

neuroscience↗

bioRxiv2026

Precision Confidence Mapping: An approach to determining individualized network topography with limited data

Individualized resting-state functional magnetic resonance imaging (rs-fMRI) is increasingly used to guide neuromodulation target selection. However, clinical scans are often short and noisy, and standard pipelines for functional network identification do not provide information about confidence of network assignment. With limited data, unstable network assignments can misdirect stimulation toward off-target regions, making it critical to know which assignments can be trusted. We developed Precision Confidence Mapping (PCM), a bootstrap-based framework that makes this uncertainty explicit and actionable. PCM repeatedly resamples the time series and reruns network detection to estimate how consistently each vertex is assigned to a given network. The resulting confidence maps can be thresholded to exclude less stable regions. We evaluated PCM across scan durations from 5 to 70 minutes using positive predictive value (PPV) as the primary measure of network-assignment precision. PPV quantified the proportion of vertices assigned to a network that received the same label in an independent within-subject 70 minute reference map. Confidence thresholding markedly improved PPV across functional networks, with the largest gains for short scan durations. Compared with standard network assignment, PCM significantly increased agreement with this independent reference. Within-subject agreement remained greater than between-subject agreement, indicating that thresholding preserved individual-specific network topography. These precision gains came with modest reductions in reference-network coverage, particularly at shorter scan durations. This tradeoff may be acceptable for neuromodulation applications that prioritize minimizing off-network assignments. By adding a reliability layer to individualized mapping, PCM supports more cautious and precise neuromodulation targeting under real-world clinical scan constraints.

neuroscience↗

bioRxiv2026

Functional brain organization is stable within individuals across years

Brain regions exhibit dynamic yet highly coordinated activity patterns that form large-scale functional networks measurable through resting-state correlations. While their association with fluctuating activity may intuitively suggest functional networks to be temporally transient and dependent on state, a growing body of literature suggests that they are person-specific and stable across days. If truly person-specific, then functional networks should preserve unique characteristics over extended periods. To test this hypothesis, we collected longitudinal precision fMRI data ([≥]60 minutes per participant per time point) from 10 healthy young adults across 1-3 year intervals, as well as three adults over 8-13 years. We further replicated findings in the MyConnectome dataset and its 10-year follow-up. Functional network organization--when sufficient per-participant data were collected-- remained largely stable within individuals over prolonged periods of up to 13 years, suggesting that individualized brain organization constitutes persistent features of personal identity that may be supported by homeostatic mechanisms. SIGNIFICANCEWhile many aspects of brain function are portrayed as dynamic and malleable, our study provides evidence for the long-term preservation of functional organization of the healthy young adult brain. Whole-brain functional organization exhibited unique individual characteristics that were preserved for years, even over a decade. The stability of such individualized neural architecture suggests that the brain encodes features of personhood that may be invariant across contexts and temporal fluctuations. This observation reframes our understanding of brain resilience and plasticity by offering new insights into the extent that homeostatic mechanisms of brain organization can withstand stressors and environmental changes through time to maintain a constant functional organization. These insights pave the way for a more comprehensive understanding of the neural mechanisms behind this stability, with the possibility of pinpointing critical markers of healthy brain function and its disruptions.

neuroscience↗

bioRxiv2026

Functional brain network correlates of pubertal timing and depressive symptoms in preadolescence

BACKGROUNDVariation in pubertal maturation relative to same-age, same-sex peers (pubertal timing) has been linked to increased risk for depressive symptoms during adolescence. This developmental period is also characterized by substantial reorganization of functional brain networks. However, how pubertal timing relates to resting-state functional connectivity (rsFC) changes and depression risk remains unclear. METHODSWe examined pubertal timing and rsFC associations in preadolescents aged 9-11 years from the Adolescent Brain Cognitive Development (ABCD) Study. Pubertal timing was estimated using a puberty age gap approach based on parent-reported physical development. Linear mixed-effects and Bayesian multilevel models were used to assess cross-sectional and longitudinal associations between pubertal timing and rsFC across large-scale functional brain networks. We also tested whether rsFC differences explained associations between pubertal timing and later depressive symptoms. RESULTSEarlier pubertal timing was associated with heterogeneous rsFC patterns, with stronger and more widespread effects in females. In females, earlier pubertal timing was associated with rsFC increases and decreases across sensory-motor and association networks, whereas in males, associations were more limited and localized to sensorimotor and cerebellar systems. Longitudinally, earlier pubertal timing in females predicted reductions in rsFC at the 2-year follow-up, with no significant associations in males. rsFC differences did not explain the pubertal timing and later depressive symptoms association. CONCLUSIONSPubertal timing is associated with sex-specific patterns of brain functional connectivity during early adolescence, with greater heterogeneity and broader network involvement in females. These findings suggest that pubertal maturation contributes to early reorganization of functional brain networks, although these changes did not explain subsequent depressive symptoms.

neuroscience↗

bioRxiv2026

Robust lesion network mapping reveals genuine symptom-specific networks

Lesion network mapping (LNM) and its derivatives successfully integrate anatomically distributed brain loci into common symptom-associated functional networks, however, their statistical validity and specificity have recently become topics of debate. Here, we introduce a null model-based robust LNM (rLNM) framework to perform sensitivity and symptom-specificity testing. Across multiple lesion-based (10 conditions, 333 lesions) and task-based (4 conditions, 706 experiments) datasets, rLNM reveals biologically meaningful and symptom-specific networks while effectively controlling for false positives.

neuroscience↗

bioRxiv2026

Parallel processing chains span cytoarchitectures to organize association cortex

Task fMRI1 and electrophysiology2 have revealed distributed, linked cortical patches with shared category preferences (e.g., faces, objects, places)1,3-5, smaller than cytoarchitectonic areas. Resting-state functional connectivity (RSFC) similarly showed that somato-cognitive action network (SCAN) nodes interleave with effectors (foot, hand, mouth), subdividing the precentral gyrus6. Here, using multiple precision functional mapping (PFM) modalities (RSFC, task, lags), we discovered that most of association cortex is organized like face processing and SCAN, with small, discrete patches interconnected into chains. Such patch-chains densely tile prefrontal cortex but are largely absent from primary cortex. Cortico-striatal connectivity is organized such that patches of the same chain connect to the same striatal location. Within chains, infra-slow fMRI signals are ordered in time. RSFC-defined chains align with task fMRI localizers (e.g., visual, motor, pain). Chains are absent at birth and emerge in the first year of life, suggesting their formation is at least partially experience-driven. Cytoarchitectonic areas are subdivided by patches, and patches in the same chain are distributed across different cytoarchitectures. Chains represent parallel ordered processing streams that are separated by information domain and behavioral goals, not cytoarchitectonics. Functional subdivision of architectonics into smaller patches, interlinked to form cross-architecture chains, enable greater parallelization and flexible specialization of processing.

neuroscience↗

bioRxiv2026

Gliomas preferentially develop within the action-mode network

Gliomas tend to arise in specific brain regions and may integrate into functional circuits, suggesting they could be regulated by brain activity. However, it remains unclear whether glioma growth is related to system-level brain networks. Analyzing neuroimaging data from three datasets including 1,310 patients with cerebral gliomas, we identified and replicated a functionally connected glioma network, which overlaps with the action-mode network (AMN), somatomotor network (SMN), and action-related subcortical regions. Resting-state functional connectivity (RSFC) of the AMN successfully predicted the location of glioma occurrence in two independent datasets with complex tumor distributions. Remarkably, no patient had a glioma entirely outside the AMN, and over 89% of patients exhibited gliomas with at least 50% overlap with the network. Moreover, the spatial overlap between glioma location and the AMN demonstrated significant prognostic value in survival analyses, with higher AMN-tumor overlap associated with poorer overall survival. Notably, the acetylcholine transporter, a key player in glioma pathogenesis that drives transcriptional reprogramming, showed an expression pattern overlapping with the AMN. Meta-analytic annotations further linked the glioma network to processes of action initiation, execution, and feedback. These findings indicate that gliomas preferentially arise in circuits involved in action and highlight the central role of the AMN in glioma pathophysiology and growth.

neuroscience↗

bioRxiv2025

Stimulant medications affect arousal and reward, not attention

Prescription stimulants such as methylphenidate are being used by an increasing portion of the population, primarily children. These potent norepinephrine and dopamine reuptake inhibitors promote wakefulness, suppress appetite, enhance physical performance, and are purported to increase attentional abilities. Prior functional magnetic resonance imaging (fMRI) studies have yielded conflicting results about the effects of stimulants on the brains attention, action/motor, and salience regions that are difficult to reconcile with their proposed attentional effects. Here, we utilized resting-state fMRI (rs-fMRI) data from the large Adolescent Brain Cognitive Development (ABCD) Study to understand the effects of stimulants on brain functional connectivity (FC) in children (n = 11,875; 8-11 years old) using network level analysis (NLA). We validated these brain-wide association study (BWAS) findings in a controlled, precision imaging drug trial (PIDT) with highly-sampled (165-210 minutes) healthy adults receiving high-dose methylphenidate (Ritalin, 40 mg). In both studies, stimulants were associated with altered FC in action and motor regions, matching patterns of norepinephrine transporter expression. Connectivity was also changed in the salience (SAL) and parietal memory networks (PMN), which are important for reward-motivated learning and closely linked to dopamine, but not the brains attention systems (e.g. dorsal attention network, DAN). Stimulant-related differences in FC closely matched the rs-fMRI pattern of getting enough sleep, as well as EEG- and respiration-derived brain maps of arousal. Taking stimulants rescued the effects of sleep deprivation on brain connectivity and school grades. The combined noradrenergic and dopaminergic effects of stimulants may drive brain organization towards a more wakeful and rewarded configuration, explaining improved task effort and persistence without direct effects on attention networks.

neuroscience↗

bioRxiv2025

Dense Longitudinal Precision Neuroimaging of Recovery from Traumatic Brain Injury

Traumatic brain injury (TBI) disrupts white matter tracts essential for cognition and emotion. Diffusion tensor imaging (DTI) can noninvasively measure white matter integrity. However, DTI has been inconsistent in predicting patient recovery from TBI, possibly due to the complex, dynamic, and individual-specific process of post-TBI white matter remodeling. Here, we employed dense longitudinal neuroimaging to track white matter recovery weekly over six months after a TBI within a single patient and a control in a similar age group (21 vs. 24 y.o.). In the patient, but not in the control, DTI metrics precisely tracked parabolic trajectories across time, with early structural alterations continuing for more than 15 weeks before reversing direction. The extent of alteration in each tract was correlated with the time until reversal. These continuous DTI changes also mediated recovery of cognitive and emotional function, suggesting they are not passive markers of damage but dynamic processes underlying functional improvement. Complementary diffusion basis spectrum imaging (DBSI) revealed an initial phase of cellular loss followed by inflammatory remodeling, vascular adaptations, and persistent metabolic activity. Our findings indicate that recovery does not follow predefined phases but rather individualized transition points, which could define optimal windows for rehabilitation. Identifying these inflection points may enable personalized interventions aligned with biologically relevant structural shifts, rather than broad recovery periods.

neuroscience↗

bioRxiv2024

Brain functional connectivity, but not neuroanatomy, captures the interrelationship between sex and gender in preadolescents

Understanding sex differences in the adolescent brain is crucial, as these differences are linked to neurological and psychiatric conditions that vary between males and females. Predicting sex from adolescent brain data may offer valuable insights into how these variations shape neurodevelopment. Recently, attention has shifted toward exploring socially-identified gender, distinct from sex assigned at birth, recognizing its additional explanatory power. This study evaluates whether resting-state functional connectivity (rsFC) or cortical thickness more effectively predicts sex and sex/gender alignment (the congruence between sex and gender) and investigates their interrelationship in preadolescents. Using data from the Adolescent Brain Cognitive Development (ABCD) Study, we employed machine learning to predict both sex (assigned at birth) and sex/gender alignment from rsFC and cortical thickness. rsFC predicted sex with significantly higher accuracy (86%) than cortical thickness (75%) and combining both did not improve the rsFC models accuracy. Brain regions most effective in predicting sex belonged to association (default mode, dorsal attention, and parietal memory) and visual (visual and medial visual) networks. The rsFC sex classifier trained on sex/gender aligned youth was significantly more effective in classifying unseen youth with sex/gender alignment than in classifying unseen youth with sex/gender unalignment. In females, the degree to which their brains rsFC matched a sex profile (female or male), was positively associated with the degree of sex/gender alignment. Lastly, neither rsFC nor cortical thickness predicted sex/gender alignment. These findings highlight rsFCs predictive power in capturing the relationship between sex and gender and the complexity of the interplay between sex, gender, and the brains functional connectivity and neuroanatomy.

neuroscience↗

bioRxiv2024

MRI economics: Balancing sample size and scan duration in brain wide association studies

A pervasive dilemma in brain-wide association studies (BWAS) is whether to prioritize functional MRI (fMRI) scan time or sample size. We derive a theoretical model showing that individual-level phenotypic prediction accuracy increases with sample size and total scan duration (sample size x scan time per participant). The model explains empirical prediction accuracies extremely well across 76 phenotypes from nine resting-fMRI and task-fMRI datasets (R2 = 0.89), spanning a wide range of scanners, acquisitions, racial groups, disorders and ages. For scans [≤]20 mins, prediction accuracy increases linearly with the logarithm of total scan duration, suggesting interchangeability of sample size and scan time. However, sample size is ultimately more important than scan time in determining prediction accuracy. Nevertheless, when accounting for overhead costs associated with each participant (e.g., recruitment costs), to boost prediction accuracy, longer scans can yield substantial cost savings over larger sample size. To achieve high prediction performance, 10-min scans are highly cost inefficient. In most scenarios, the optimal scan time is [≥]20 mins. On average, 30-min scans are the most cost-effective, yielding 22% cost savings over 10-min scans. Overshooting is cheaper than undershooting the optimal scan time, so we recommend aiming for [≥]30 mins. Compared with resting-state whole-brain BWAS, the most cost-effective scan time is shorter for task-fMRI and longer for subcortical-cortical BWAS. Standard power calculations maximize sample size at the expense of scan time. Our study demonstrates that optimizing both sample size and scan time can boost prediction power while cutting costs. Our empirically informed reference is available for future study planning: WEB_APPLICATION_LINK

neuroscience↗

bioRxiv2024

The brainstem's red nucleus was evolutionarily upgraded to support goal-directed action

The red nucleus is a large brainstem structure that coordinates limb movement for locomotion in quadrupedal animals (Basile et al., 2021). The humans red nucleus has a different pattern of anatomical connectivity compared to quadrupeds, suggesting a unique purpose (Hatschek, 1907). Previously the function of the human red nucleus remained unclear at least partly due to methodological limitations with brainstem functional neuroimaging (Sclocco et al., 2018). Here, we used our most advanced resting-state functional connectivity (RSFC) based precision functional mapping (PFM) in highly sampled individuals (n = 5) and large group-averaged datasets (combined N [~] 45,000), to precisely examine red nucleus functional connectivity. Notably, red nucleus functional connectivity to motor-effector networks (somatomotor hand, foot, and mouth) was minimal. Instead, red nucleus functional connectivity along the central sulcus was specific to regions of the recently discovered somato-cognitive action network (SCAN; (Gordon et al., 2023)). Outside of primary motor cortex, red nucleus connectivity was strongest to the cingulo-opercular (CON) and salience networks, involved in action/cognitive control (Dosenbach et al., 2007; Newbold et al., 2021) and reward/motivated behavior (Seeley, 2019), respectively. Functional connectivity to these two networks was organized into discrete dorsal-medial and ventral-lateral zones. Red nucleus functional connectivity to the thalamus recapitulated known structural connectivity of the dento-rubral thalamic tract (DRTT) and could prove clinically useful in functionally targeting the ventral intermediate (VIM) nucleus. In total, our results indicate that far from being a motor structure, the red nucleus is better understood as a brainstem nucleus for implementing goal-directed behavior, integrating behavioral valence and action plans.

neuroscience↗

bioRxiv2023

Framewise multi-echo distortion correction for superior functional MRI

Functional MRI (fMRI) data are severely distorted by magnetic field (B0) inhomogeneities which currently must be corrected using separately acquired field map data. However, changes in the head position of a scanning participant across fMRI frames can cause changes in the B0 field, preventing accurate correction of geometric distortions. Additionally, field maps can be corrupted by movement during their acquisition, preventing distortion correction altogether. In this study, we use phase information from multi-echo (ME) fMRI data to dynamically sample distortion due to fluctuating B0 field inhomogeneity across frames by acquiring multiple echoes during a single EPI readout. Our distortion correction approach, MEDIC (Multi-Echo DIstortion Correction), accurately estimates B0 related distortions for each frame of multi-echo fMRI data. Here, we demonstrate that MEDICs framewise distortion correction produces improved alignment to anatomy and decreases the impact of head motion on resting-state functional connectivity (RSFC) maps, in higher motion data, when compared to the prior gold standard approach (i.e., TOPUP). Enhanced framewise distortion correction with MEDIC, without the requirement for field map collection, furthers the advantage of multi-echo over single-echo fMRI.

bioengineering↗

bioRxiv2023

Disuse-driven plasticity in the human thalamus and putamen

Motor adaptation in cortico-striato-thalamo-cortical loops has been studied mainly in animals using invasive electrophysiology. Here, we leverage functional neuroimaging in humans to study motor circuit plasticity in the human subcortex. We employed an experimental paradigm that combined two weeks of upper-extremity immobilization with daily resting-state and motor task fMRI before, during, and after the casting period. We previously showed that limb disuse leads to decreased functional connectivity (FC) of the contralateral somatomotor cortex (SM1) with the ipsilateral somatomotor cortex, increased FC with the cingulo-opercular network (CON) as well as the emergence of high amplitude, fMRI signal pulses localized in the contralateral SM1, supplementary motor area and the cerebellum. From our prior observations, it remains unclear whether the disuse plasticity affects the thalamus and striatum. We extended our analysis to include these subcortical regions and found that both exhibit strengthened cortical FC and spontaneous fMRI signal pulses induced by limb disuse. The dorsal posterior putamen and the central thalamus, mainly CM, VLP and VIM nuclei, showed disuse pulses and FC changes that lined up with fmri task activations from the Human connectome project motor system localizer, acquired before casting for each participant. Our findings provide a novel understanding of the role of the cortico-striato-thalamo-cortical loops in human motor plasticity and a potential link with the physiology of sleep regulation. Additionally, similarities with FC observation from Parkinson Disease (PD) questions a pathophysiological link with limb disuse.

neuroscience↗

bioRxiv2023

Substructure of the brain's Cingulo-Opercular network

The Cingulo-Opercular network (CON) is an executive network of the human brain that regulates actions. CON is composed of many widely distributed cortical regions that are involved in top-down control over both lower-level (i.e., motor) and higher-level (i.e., cognitive) functions, as well as in processing of painful stimuli. Given the topographical and functional heterogeneity of the CON, we investigated whether subnetworks within the CON support separable aspects of action control. Using precision functional mapping (PFM) in 15 participants with > 5 hours of resting state functional connectivity (RSFC) and task data, we identified three anatomically and functionally distinct CON subnetworks within each individual. These three distinct subnetworks were linked to Decisions, Actions, and Feedback (including pain processing), respectively, in convergence with a meta-analytic task database. These Decision, Action and Feedback subnetworks represent pathways by which the brain establishes top-down goals, transforms those goals into actions, implemented as movements, and processes critical action feedback such as pain.

neuroscience↗

bioRxiv2023

Structure-Function Coupling in Highly Sampled Individual Brains

Structural connections (SC) between distant regions of the brain support synchronized function known as functional connectivity (FC) and give rise to the large-scale brain networks that enable cognition and behavior. Understanding how SC enables FC is important to understand how injuries to structural connections may alter brain function and cognition. Previous work evaluating whole-brain SC-FC relationships showed that SC explained FC well in unimodal visual and motor areas, but only weakly in association areas, suggesting a unimodal-heteromodal gradient organization of SC-FC coupling. However, this work was conducted in group-averaged SC/FC data. Thus, it could not account for inter-individual variability in the locations of cortical areas and white matter tracts. We evaluated the correspondence of SC and FC within three highly sampled healthy participants. For each participant, we collected 78 minutes of diffusion-weighted MRI for SC and 360 minutes of resting state fMRI for FC. We found that FC was best explained by SC in visual and motor systems, as well as in anterior and posterior cingulate regions. A unimodal-to-heteromodal gradient could not fully explain SC-FC coupling. We conclude that the SC-FC coupling of the anterior-posterior cingulate circuit is more similar to unimodal areas than to heteromodal areas. SIGNIFICANCE STATEMENTStructural connections between distant regions of the human brain support networked function that enables cognition and behavior. Improving our understanding of how structure enables function could allow better insight into how brain disconnection injuries impair brain function. Previous work using neuroimaging suggested that structure-function relationships vary systematically across the brain, with structure better explaining function in basic visual/motor areas than in higher-order areas. However, this work was conducted in group-averaged data, which may obscure details of individual-specific structure-function relationships. Using individual-specific densely sampled neuroimaging data, we found that in addition to visual/motor regions, structure strongly predicts function in specific circuits of the higher-order cingulate gyrus. The cingulates structure-function relationship suggests that its organization may be unique among higher-order cortical regions.

neuroscience↗

bioRxiv2021

Real-time motion monitoring improves functional MRI data quality in infants

Imaging the infant brain with MRI has improved our understanding of early stages of neurodevelopment. However, head motion during MRI acquisition is detrimental to both functional and structural MRI scan quality. Though infants are commonly scanned while asleep, they commonly exhibit motion during scanning, causing data loss. Our group has shown that providing MRI technicians with real-time motion estimates via Framewise Integrated Real-Time MRI Monitoring (FIRMM) software helps obtain high-quality, low motion fMRI data. By estimating head motion in real time and displaying motion metrics to the MR technician during an fMRI scan, FIRMM can improve scanning efficiency. Hence, we compared average framewise displacement (FD), a proxy for head motion, and the amount of usable fMRI data (FD [≤] 0.2mm) in infants scanned with (n = 407) and without FIRMM (n = 295). Using a mixed-effects model, we found that the addition of FIRMM to current state-of-the-art infant scanning protocols significantly increased the amount of usable fMRI data acquired per infant, demonstrating its value for research and clinical infant neuroimaging.

neuroscience↗

bioRxiv2021

Precision dynamical mapping using topological data analysis reveals a unique hub-like transition state at rest

Even in the absence of external stimuli, neural activity is both highly dynamic and organized across multiple spatiotemporal scales. The continuous evolution of brain activity patterns during rest is believed to help maintain a rich repertoire of possible functional configurations that relate to typical and atypical cognitive phenomena. Whether these transitions or "explorations" follow some underlying arrangement or instead lack a predictable ordered plan remains to be determined. Here, using a precision dynamics approach, we aimed at revealing the rules that govern transitions in brain activity at rest at the single participant level. We hypothesized that by revealing and characterizing the overall landscape of whole brain configurations (or states) we could interpret the rules (if any) that govern transitions in brain activity at rest. To generate the landscape of whole-brain configurations we used Topological Data Analysis based Mapper approach. Across all participants, we consistently observed a rich topographic landscape in which the transition of activity from one state to the next involved a central hub-like "transition state." The hub topography was characterized as a shared attractor-like basin where all canonical resting-state networks were represented equally. The surrounding periphery of the landscape had distinct network configurations. The intermediate transition state and traversal through it via a topographic gradient seemed to provide the underlying structure for the continuous evolution of brain activity patterns at rest. In addition, differences in the landscape architecture were more consistent within than between subjects, providing evidence of idiosyncratic dynamics and potential utility in precision medicine.

neuroscience↗