Biology subjects

Gratton, C.

Publications and source records attributed to Gratton, C..

At least 19 recordsLinked to original sources

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

Bumble Bee Abundance and Diversity Increase with Intensity of Tallgrass Prairie Restoration Intervention

IntroductionHuman land-use intensification and the resulting habitat loss are primary drivers of insect pollinator declines. Habitat restoration offers a promising approach to counteract these declines, yet landscape-level evaluations of bee responses to restoration and management remain limited. We conducted a two-year, landscape-scale study in Wisconsin, USA, to assess how different intensities of tallgrass prairie restoration and management affect bumble bees (Bombus spp.). ObjectivesThis study aimed to determine whether (1) bumble bee abundance and diversity increase with assisted restoration, and (2) outcomes differ between low-(seeded only) and moderate-intensity (seeded and managed with prescribed fire) interventions. MethodsUsing catch-and-release surveys, we measured bumble bee abundance and diversity at 32 sites representing a gradient in restoration intervention: no intervention (unassisted recovery), low intervention, and moderate intervention. ResultsBumble bee abundance and diversity were higher at assisted restoration sites (low and moderate intervention) than at unassisted sites. Although both tended to be greater at moderate than low intervention intensities, these differences were not statistically significant. Bumble bee community composition also differed across intervention intensity, driven by shifts in dominant species (e.g., B. impatiens and B. griseocollis). Rarer taxa, including endangered and vulnerable species, occurred only at assisted restoration sites, with the largest populations at moderate intervention sites. Across all sites, bumble bee responses were strongly and positively associated with floral abundance, but not with semi-natural habitat in the surrounding landscape. ConclusionOur findings demonstrate that assisted grassland restoration can effectively increase bumble bee abundance and diversity, supporting its value as a conservation practice for pollinators. Implications for Practice: (1) Grassland restorations targeting plant communities can successfully support nontarget pollinators across a range of management intensities and landscape contexts. Adding seeds of pollinator-preferred plants could improve restorations with low floral abundance and diversity. (2) Management of existing restorations is important to maintain abundant floral resources and diverse pollinator communities. Because sites varied widely in prescribed fire use, our findings likely represent a conservative estimate of its benefits, and higher intervention intensity (e.g., repeated seeding, regular fire, mechanical or chemical shrub and invasive plants control) may further enhance outcomes for bumble bees.

ecology↗

bioRxiv2025

Precision fMRI reveals densely interdigitated network patches with conserved motifs in the lateral prefrontal cortex

Dominant models of human lateral prefrontal cortex (LPFC) organization emphasize broad domain-general zones and smooth functional gradients. However, these models rely heavily on group-averaged neuroimaging, which can obscure fine-scale cortical features - especially in highly inter-individually variable regions like the LPFC. To address this limitation, we collected a new precision fMRI dataset from 10 individuals, each with approximately 2 hours of resting-state and 6 hours of task data. We mapped individual-specific LPFC networks using resting-state fMRI and tested network-level functional preferences using task fMRI. We found that individual LPFC organization differed markedly from group-averaged estimates. Individual maps showed more fragmented and interdigitated networks - especially in anterior LPFC - including novel conserved motifs present across individuals. Task fMRI revealed that distinct but adjacent networks support domain-specific processes (i.e., language, social cognition, episodic projection) versus domain-general control. Sharp functional boundaries were visible at the individual level that could not be observed in group data. These findings uncover previously hidden organizational principles in the LPFC and offer a framework for understanding how the LPFC supports flexible, complex cognition through a finely organized architecture.

neuroscience↗

bioRxiv2025

Precision functional mapping reveals less inter-individual variability in the child vs. adult human brain

Human brain organization shares a common underlying structure, though recent studies have shown that features of this organization also differ significantly across individual adults. Understanding the developmental pathways that lead to individually unique brains is important for advancing models of cognitive development and neurodevelopmental disorders. Here we use highly personalized precision neuroimaging methods to map brain networks within 12 individual children, ages 8-12 years. We demonstrate fMRI functional connectivity maps that substantially exceed the reliability of traditional techniques, allowing us to measure individual differences after overcoming biases from measurement noise. Children share core functional network topography, with greatest inter-individual variability in association regions, consistent with adult findings. However, children show less between-subject variability than adults, suggesting increasing individual differentiation in brain networks with development. This pediatric precision neuroimaging dataset is publicly available to support future brain development research and provides a high-fidelity foundation for studying individual variation in atypical development.

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bioRxiv2025

Towards Precision Functional Brain Network Mapping in Parkinsons Disease

BackgroundParkinsons disease (PD) is a complex neurodegenerative condition that leads to widespread disruption of large-scale brain networks and is further complicated by substantial individual variability in symptomology, progression rates, and treatment response. Consequently, the investigation of individual differences in networks measured via resting state functional connectivity (RSFC) may provide insight. However, most RSFC studies are unable to identify interindividual differences due to poor reliability and group average network definitions. "Precision" RSFC addresses these shortcomings through extended data collection, strict denoising, and individual network definition, but remains untested in PD. ObjectivesTo evaluate the feasibility and reliability of precision RSFC studies in PD. MethodsWe collected >100 minutes of RSFC data from 20 PD and 6 healthy controls participants. We evaluated the level of motion, reliability and stability of RSFC measures in each participant and contrasted these measures between the PD and HC groups, as well as compared to a conventional 5 minutes of RSFC data. In addition, we created individualized brain network measures in PD participants to establish feasibility in this population. ResultsUsing precision methods, the PD group produced reliable and stable RSFC measures of brain networks of similar quality to healthy controls and substantially better than conventional methods. Individualized network maps from individuals with PD demonstrate differences from group averages and from each other, including in key motor systems. ConclusionPrecision RSFC is feasible and reliable in individuals with PD. This approach holds promise for advancing personalized diagnostics and identifying brain-based biomarkers underlying clinical variability in PD.

neuroscience↗

bioRxiv2025

Longitudinal Stability of Mood-Related Resting-State Networks in Youth with Symptomatic Bipolar-I/II Disorder

Bipolar disorder (BD) is characterized by temporal instability of mood and energy, but the neural correlates of this instability are poorly understood. In previous cross-sectional studies, mood state in BD has been associated with differential functional connectivity (FC) amongst several subcortical regions and ventromedial prefrontal cortex. Here, we assess whether BD is associated with longitudinal instability within this mood-related network of interest (NOI). Young people with BD-I/II were scanned 4-6 times and healthy controls (HC) were scanned 4 times over 9 months. Following preprocessing of 20-minute resting-state scans, we assessed across-scan correlation of FC, focusing on FC between regions previously associated with BD mood state. Utilizing Bayesian models, we assessed the relationship between diagnostic group and within-person, across-scan correlation, adjusting for motion, time-of-day, and inter-scan interval; prediction intervals (PI) are reported. In a sample of 16 youth (11 BD, 5 HC; 16.3-23.3 years old) with 70 scans (50 BD, 20 HC), across-scan NOI stability was higher within-than between-person (0.70 vs. 0.54; p<.0001). BD (vs. HC) within-person scan-pairs showed lower NOI stability (mean -0.109; 95% PI -0.181, -0.038), distinguishing BD vs. HC with excellent accuracy (AUC=0.95). NOI instability was more pronounced with manic symptoms (mean -0.012; 95% PI -0.023, -0.0002) and in BD-II (vs. BD-I; mean -0.071; 90% PI -0.136, -0.007). Results persisted after accounting for medications, comorbidity, and sleep/arousal measures. Within this pilot sample, BD is characterized by less within-person stability of a mood-related NOI. While preliminary, these results highlight a possible role for precision imaging approaches to elucidate neural mechanisms underlying BD.

neuroscience↗

bioRxiv2024

A network correspondence toolbox for quantitative evaluation of novel neuroimaging results

Decades of neuroscience research has shown that macroscale brain dynamics can be reliably decomposed into a subset of large-scale functional networks, but the specific spatial topographies of these networks and the names used to describe them can vary across studies. Such discordance has hampered interpretation and convergence of research findings across the field. To address this problem, we have developed the Network Correspondence Toolbox (NCT) to permit researchers to examine and report spatial correspondence between their novel neuroimaging results and sixteen widely used functional brain atlases, consistent with recommended reporting standards developed by the Organization for Human Brain Mapping. The atlases included in the toolbox show some topographical convergence for specific networks, such as those labeled as "default" or "visual". Network naming varies across atlases, particularly for networks spanning frontoparietal association cortices. For this reason, quantitative comparison with multiple atlases is recommended to benchmark novel neuroimaging findings. We provide several exemplar demonstrations using the Human Connectome Project task fMRI results and UK Biobank independent component analysis maps to illustrate how researchers can use the NCT to report their own findings through quantitative evaluation against multiple published atlases. The NCT provides a convenient means for computing Dice coefficients with spin test permutations to determine the magnitude and statistical significance of correspondence among user-defined maps and existing atlas labels. The NCT also includes functionality to incorporate additional atlases in the future. The adoption of the NCT will make it easier for network neuroscience researchers to report their findings in a standardized manner, thus aiding reproducibility and facilitating comparisons between studies to produce interdisciplinary insights.

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bioRxiv2023

Homogenization of taxonomic, phylogenetic, and functional characteristics of bumble bee communities at regional scales in anthropogenic landscapes

Biotic homogenization has been documented following extensive anthropogenic landscape change such as urbanization and agriculture, but diverse native communities also have been reported in these ecosystems. Understanding the influence of landscape-level characteristics on processes of community assembly can inform how human-dominated landscapes shape the structure and composition of local communities, including important pollinators such as bumble bees (Bombus spp.). The objective of this study was to investigate multi-scale patterns of taxonomic, phylogenetic, and functional beta- diversity of bumble bees in greenspaces along an urban-agricultural gradient to understand landscape- scale constraints on processes of community assembly. Bumble bees were collected in greenspaces along an urban-agricultural gradient in Madison, WI, USA. Patterns of biotic homogenization were investigated using measures of beta-diversity and null models relative to a regional bumble bee species pool in a 100 km area surrounding the city. Nine of the expected 13 species from the regional pool were collected in greenspaces in urban and agricultural landscapes. At the regional scale, we found evidence of taxonomic, phylogenetic, and functional homogenization among bumble bee communities in urban and agricultural landscapes, with species that were smaller in size, had shorter wings, were less hairy, but had larger eyes and longer setae on the corbicula (pollen-carrying hind legs) being more common than expected based on null models. When we evaluated filtering from the anthropogenic species pools (i.e., urban and agricultural) to local greenspaces, we found nuanced differences among land cover types, wherein agricultural landscapes supported higher beta-diversity of bumble bee communities than expected while urban landscapes continued to show signals of homogenization. Overall, anthropogenic landscapes acted as a strong filter for bumble bees, broadly selecting for a subset of functionally similar and phylogenetically related species that resulted in homogenization of communities within the region. Our findings support a landscape-level approach to biodiversity conservation that promotes diversifying landscapes to support diverse pollinator populations. OPEN RESEARCH STATEMENTData and novel code associated with this submission are provided in an external repository to be evaluated during the peer review process and are available at https://github.com/kiperry/WI_Bumble_Bees. If this paper is accepted for publication, data and code will be permanently archived within a linked Zenodo repository.

ecology↗

bioRxiv2023

Situating the parietal memory network in the context of multiple parallel distributed networks using high-resolution functional connectivity

A principle of brain organization is that networks serving higher cognitive functions are widely distributed across the brain. One exception has been the parietal memory network (PMN), which plays a role in recognition memory but is often defined as being restricted to posteromedial association cortex. We hypothesized that high-resolution estimates of the PMN would reveal small regions that had been missed by prior approaches. High-field 7T functional magnetic resonance imaging (fMRI) data from extensively sampled participants was used to define the PMN within individuals. The PMN consistently extended beyond the core posteromedial set to include regions in the inferior parietal lobule; rostral, dorsal, medial, and ventromedial prefrontal cortex; the anterior insula; and ramus marginalis of the cingulate sulcus. The results suggest that, when fine-scale anatomy is considered, the PMN matches the expected distributed architecture of other association networks, reinforcing that parallel distributed networks are an organizing principle of association cortex.

neuroscience↗

bioRxiv2023

Specialized cingulo-opercular network activation in judging ambiguity of facial expressions in a slow reveal fMRI paradigm

Cortical task control networks, including the cingulo-opercular (CO) network play a key role in decision-making across a variety of functional domains. In particular, the CO network functions in a performance reporting capacity that supports successful task performance, especially in response to errors and ambiguity. In two studies testing the contribution of the CO network to ambiguity processing, we presented a valence bias task in which masked clearly and ambiguously valenced emotional expressions were slowly revealed over several seconds. This slow reveal task design provides a window into the decision-making mechanisms as they unfold over the course of a trial. In the main study, the slow reveal task was administered to 32 young adults in the fMRI environment and BOLD time courses were extracted from regions of interest in three control networks. In a follow-up study, the task was administered to a larger, online sample (n = 81) using a more extended slow reveal design with additional unmasking frames. Positive judgments of surprised faces were uniquely accompanied by slower response times and strong, late activation in the CO network. These results support the initial negativity hypothesis, which posits that the default response to ambiguity is negative and positive judgments are associated with a more effortful controlled process, and additionally suggests that this controlled process is mediated by the CO network. Moreover, ambiguous trials were characterized by a second CO response at the end of the trial, firmly placing CO function late in the decision-making process.

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bioRxiv2022

A mind-body interface alternates with effector-specific regions in motor cortex

Primary motor cortex (M1) has been thought to form a continuous somatotopic homunculus extending down precentral gyrus from foot to face representations1,2. The motor homunculus has remained a textbook pillar of functional neuroanatomy, despite evidence for concentric functional zones3 and maps of complex actions4. Using our highest precision functional magnetic resonance imaging (fMRI) data and methods, we discovered that the classic homunculus is interrupted by regions with sharpy distinct connectivity, structure, and function, alternating with effector-specific (foot, hand, mouth) areas. These inter-effector regions exhibit decreased cortical thickness and strong functional connectivity to each other, and to prefrontal, insular, and subcortical regions of the Cingulo-opercular network (CON), critical for executive action5 and physiological control6, arousal7, and processing of errors8 and pain9. This interdigitation of action control-linked and motor effector regions was independently verified in the three largest fMRI datasets. Macaque and pediatric (newborn, infant, child) precision fMRI revealed potential cross-species analogues and developmental precursors of the inter-effector system. An extensive battery of motor and action fMRI tasks documented concentric somatotopies for each effector, separated by the CON-linked inter-effector regions. The inter-effector regions lacked movement specificity and co-activated during action planning (coordination of hands and feet), and axial body movement (e.g., abdomen, eyebrows). These results, together with prior work demonstrating stimulation-evoked complex actions4 and connectivity to internal organs (e.g., adrenal medulla)10, suggest that M1 is punctuated by an integrative system for implementing whole-body action plans. Thus, two parallel systems intertwine in motor cortex to form an integrate-isolate pattern: effector-specific regions (foot, hand, mouth) for isolating fine motor control, and a mind-body interface (MBI) for the integrative whole-organism coordination of goals, physiology, and body movement.

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bioRxiv2022

From Correlation to Communication: disentangling hidden factors from functional connectivity changes

While correlations in the BOLD fMRI signal are widely used to capture functional connectivity (FC) and its changes across contexts, its interpretation is often ambiguous. The entanglement of multiple factors including local coupling of two neighbors and non-local inputs from the rest of the network (affecting one or both regions) limits the scope of the conclusions that can be drawn from correlation measures alone. Here we present a method of estimating the contribution of non-local network input to FC changes across different contexts. To disentangle the effect of task-induced coupling change from the network input change, we propose a new metric, "communication change", utilizing BOLD signal correlation and variance. With a combination of simulation and empirical analysis, we demonstrate that 1) input from the rest of the network accounts for a moderate but significant amount of task-induced FC change; 2) the proposed "communication change" is a promising candidate for tracking the local coupling in task context-induced change. Additionally, when compared to FC change across three different tasks, communication change can better discriminate specific task types. Taken together, this novel index of local coupling may have many applications in improving our understanding of local and widespread interactions across large-scale functional networks.

neuroscience↗

bioRxiv2022

The cingulo-opercular network is composed of two distinct sub-systems

The cingulo-opercular (CO) network and its two best studied regions - the dorsal anterior cingulate and anterior insula - have been linked to task control, but also implicated in many additional processes across cognitive, social, and emotional domains. However, most prior work investigating the CO network has used a group-average approach, which may mix signals across nearby regions that vary across individuals. Here, we reevaluate the CO networks role in task control with both task and rest fMRI, using regions with a high probability of CO network agreement across individuals. Hierarchical clustering analyses suggest heterogeneity in the CO networks task response properties, with one sub-system (CO1) showing consistency with prior task control characterizations while another sub-system (CO2) has weak task control responses, but preserved ties to pain and motor functions. Resting-state connectivity confirms subtle differences in the architecture of these two sub-systems. This evidence suggests that, when individual variation in network locations is addressed, the CO network includes (at least) two linked sub-systems with differential roles in task control and other cognitive/motor/interoceptive responses, which may help explain varied accounts of its functions. We propose that this fractionation may reflect expansion of primary CO body-oriented control functions to broader domain-general contexts.

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bioRxiv2022

Hemispheric Asymmetries of Individual Differences in Functional Connectivity

Resting-state fMRI studies have revealed that individuals exhibit stable, functionally meaningful divergences in large-scale network organization. The locations with strongest deviations (called network variants) have a characteristic spatial distribution, with qualitative evidence from prior reports suggesting that this distribution differs across hemispheres. Hemispheric asymmetries can inform us on constraints guiding the development of these idiosyncratic regions. Here, we used data from the Human Connectome Project to systematically investigate hemispheric differences in network variants. Variants were significantly larger in the right hemisphere, particularly along the frontal operculum and medial frontal cortex. Variants in the left hemisphere appeared most commonly around the temporoparietal junction. We investigated how variant asymmetries vary by functional network and how they compare with typical network distributions. For some networks, variants seemingly increase group-average network asymmetries (e.g., the group-average language network is slightly bigger in the left hemisphere and variants also appeared more frequently in that hemisphere). For other networks, variants counter the group-average network asymmetries (e.g., the default mode network is slightly bigger in the left hemisphere, but variants were more frequent in the right hemisphere). Intriguingly, left- and right-handers differed in their network variant asymmetries for the cinguloopercular and frontoparietal networks, suggesting that variant asymmetries are connected to lateralized traits. These findings demonstrate that idiosyncratic aspects of brain organization differ systematically across the hemispheres. We discuss how these asymmetries in brain organization may inform us on developmental constraints of network variants, and how they may relate to functions differentially linked to the two hemispheres.

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bioRxiv2022

BOLD cofluctuation 'events' are predicted from static functional connectivity

Recent work identified single time points ("events") of high regional cofluctuation in functional Magnetic Resonance Imaging (fMRI) which contain more large-scale brain network information than other, low cofluctuation time points. This suggested that events might be a discrete, temporally sparse signal which drives functional connectivity (FC) over the timeseries. However, a different, not yet explored possibility is that network information differences between time points are driven by sampling variability on a constant, static, noisy signal. Using a combination of real and simulated data, we examined the relationship between cofluctuation and network structure and asked if this relationship was unique, or if it could arise from sampling variability alone. First, we show that events are not discrete - there is a gradually increasing relationship between network structure and cofluctuation; [~]50% of samples show very strong network structure. Second, using simulations we show that this relationship is predicted from sampling variability on static FC. Finally, we show that randomly selected points can capture network structure about as well as events, largely because of their temporal spacing. Together, these results suggest that, while events exhibit particularly strong representations of static FC, there is little evidence that events are unique timepoints that drive FC structure. Instead, a parsimonious explanation for the data is that events arise from a single static, but noisy, FC structure. HIGHLIGHTSO_LIPast results suggested high cofluctuation BOLD "events" drive fMRI functional connectivity, FC C_LIO_LIHere, events were examined in both real fMRI data and a stationary null model to test this model C_LIO_LIIn real data, >50% of BOLD timepoints show high modularity and similarity to time- averaged FC C_LIO_LIStationary null models identified events with similar behavior to real data C_LIO_LIEvents may not be a transient driver of static FC, but rather an expected outcome of it. C_LI

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bioRxiv2022

A Precision Functional Atlas of Network Probabilities and Individual-Specific Network Topography

The brain is organized into a broad set of functional neural networks. These networks and their various characteristics have been described and scrutinized through in vivo resting state functional magnetic resonance imaging (rs-fMRI). While the basic properties of networks are generally similar between healthy individuals, there is vast variability in the precise topography across the population. These individual differences are often lost in population studies due to population averaging which assumes topographical uniformity. We leveraged precision brain mapping methods to establish a new open-source, method-flexible set of precision functional network atlases: the Masonic Institute for the Developing Brain (MIDB) Precision Brain Atlas. Using participants from the Adolescent Brain Cognitive Development (ABCD) study, single subject precision network maps were generated with two supervised network-matching procedures (template matching and non-negative matrix factorization), an overlapping template matching method for identifying integration zones, as well as an unsupervised community detection algorithm (Infomap). From these individualized maps we also generated probabilistic network maps and integration zones for two demographically-matched groups of n[~]3000 each. We demonstrate high reproducibility between groups (Pearsons r >0.999) and between methods (r=0.96), revealing both regions of high invariance and high variability. Compared to using parcellations based on groups averages, the MIDB Precision Brain Atlas allowed us to derive a set of brain regions that are largely invariant in network topography across populations, which provides more reproducible statistical maps of executive function in brain-wide associations. We also explore an example use case for probabilistic maps, highlighting their potential for use in targeted neuromodulation. The MIDB Precision Brain Atlas is expandable to alternative datasets and methods and is provided open-source with an online web interface to encourage the scientific community to experiment with probabilistic atlases and individual-specific topographies to more precisely relate network phenomenon to functional organization of the human brain.

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bioRxiv2021

Brain hubs defined in the group do not overlap with regions of high inter-individual variability

Connector hubs are brain regions with links to multiple networks. These regions are hypothesized to play a critical role in brain function. While hubs are often identified based on group-average functional magnetic resonance imaging (fMRI) data, there is considerable inter-subject variation in the functional connectivity profiles of the brain, especially in association regions where hubs tend to be located. Here we investigated how group hubs are related to locations of inter-individual variability, to better understand if hubs are (a) relatively conserved across people, (b) locations with malleable connectivity, leading individuals to show variable hub profiles, or (c) artifacts arising from cross-person variation. To answer this question, we compared the locations of hubs and regions of strong idiosyncratic functional connectivity ("variants") in both the Midnight Scan Club and Human Connectome Project datasets. Group hubs defined based on the participation coefficient did not overlap strongly with variants. These hubs have relatively strong similarity across participants and consistent cross-network profiles. Consistency across participants was further improved when participation coefficient hubs were allowed to shift slightly in local position. Thus, our results demonstrate that group hubs defined with the participation coefficient are generally consistent across people, suggesting they may represent conserved cross-network bridges. More caution is warranted with alternative hub measures, such as community density, which are based on spatial proximity and show higher correspondence to locations of individual variability.

neuroscience↗

bioRxiv2021

Two common and distinct forms of variation in human functional brain networks

The cortex has a characteristic layout with specialized functional areas forming distributed large-scale networks. However, substantial work shows striking variation in this organization across people, which relates to differences in behavior. While most prior work treats all individual differences as equivalent and primarily linked to boundary shifts between the borders of regions, here we show that cortical variants actually occur in two different forms. In addition to border shifts, variants also occur at a distance from their typical position, forming ectopic intrusions. Both forms of variants are common across individuals, but the forms differ in their location, network associations, and activations during tasks, patterns that replicate across datasets and methods of definition. Border shift variants also track significantly more with shared genetics than ectopic variants, suggesting a closer link between ectopic variants and environmental influences. Further, variant properties are categorically different between subgroups of individuals. Exploratory evidence suggests that variants can predict individual differences in behavior, but the two forms differ in which behavioral phenotypes they predict. This work argues that individual differences in brain organization commonly occur in two dissociable forms - border shifts and ectopic intrusions - suggesting that these types of variation are indexing distinct forms of cortical variation that must be separately accounted for in the analysis of cortical systems across people. This work expands our knowledge of cortical variation in humans and helps reconceptualize the discussion of how cortical systems variability arises and links to individual differences in cognition and behavior.

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