Daniel S. Margulies

YNIMG Journal 2023 Journal Article

Cortical gradients during naturalistic processing are hierarchical and modality-specific

• Ahmad Samara
• Jeffrey Eilbott
• Daniel S. Margulies
• Ting Xu
• Tamara Vanderwal

Understanding cortical topographic organization and how it supports complex perceptual and cognitive processes is a fundamental question in neuroscience. Previous work has characterized functional gradients that demonstrate large-scale principles of cortical organization. How these gradients are modulated by rich ecological stimuli remains unknown. Here, we utilize naturalistic stimuli via movie-fMRI to assess macroscale functional organization. We identify principal movie gradients that delineate separate hierarchies anchored in sensorimotor, visual, and auditory/language areas. At the opposite/heteromodal end of these perception-to-cognition axes, we find a more central role for the frontoparietal network along with the default network. Even across different movie stimuli, movie gradients demonstrated good reliability, suggesting that these hierarchies reflect a brain state common across different naturalistic conditions. The relative position of brain areas within movie gradients showed stronger and more numerous correlations with cognitive behavioral scores compared to resting state gradients. Together, these findings provide an ecologically valid representation of the principles underlying cortical organization while the brain is active and engaged in multimodal, dynamic perceptual and cognitive processing.

YNIMG Journal 2023 Journal Article

Omnipresence of the sensorimotor-association axis topography in the human connectome

• Karl-Heinz Nenning
• Ting Xu
• Alexandre R. Franco
• Khena M. Swallow
• Arielle Tambini
• Daniel S. Margulies
• Jonathan Smallwood
• Stanley J. Colcombe

Low-dimensional representations are increasingly used to study meaningful organizational principles within the human brain. Most notably, the sensorimotor-association axis consistently explains the most variance in the human connectome as its so-called principal gradient, suggesting that it represents a fundamental organizational principle. While recent work indicates these low dimensional representations are relatively robust, they are limited by modeling only certain aspects of the functional connectivity structure. To date, the majority of studies have restricted these approaches to the strongest connections in the brain, treating weaker or negative connections as noise despite evidence of meaningful structure among them. The present work examines connectivity gradients of the human connectome across a full range of connectivity strengths and explores the implications for outcomes of individual differences, identifying potential dependencies on thresholds and opportunities to improve prediction tasks. Interestingly, the sensorimotor-association axis emerged as the principal gradient of the human connectome across the entire range of connectivity levels. Moreover, the principal gradient of connections at intermediate strengths encoded individual differences, better followed individual-specific anatomical features, and was also more predictive of intelligence. Taken together, our results add to evidence of the sensorimotor-association axis as a fundamental principle of the brain's functional organization, since it is evident even in the connectivity structure of more lenient connectivity thresholds. These more loosely coupled connections further appear to contain valuable and potentially important information that could be used to improve our understanding of individual differences, diagnosis, and the prediction of treatment outcomes.

YNIMG Journal 2022 Journal Article

Disentangling cortical functional connectivity strength and topography reveals divergent roles of genes and environment

• Bianca Burger
• Karl-Heinz Nenning
• Ernst Schwartz
• Daniel S. Margulies
• Alexandros Goulas
• Hesheng Liu
• Simon Neubauer
• Justin Dauwels

The human brain varies across individuals in its morphology, function, and cognitive capacities. Variability is particularly high in phylogenetically modern regions associated with higher order cognitive abilities, but its relationship to the layout and strength of functional networks is poorly understood. In this study we disentangled the variability of two key aspects of functional connectivity: strength and topography. We then compared the genetic and environmental influences on these two features. Genetic contribution is heterogeneously distributed across the cortex and differs for strength and topography. In heteromodal areas genes predominantly affect the topography of networks, while their connectivity strength is shaped primarily by random environmental influence such as learning. We identified peak areas of genetic control of topography overlapping with parts of the processing stream from primary areas to network hubs in the default mode network, suggesting the coordination of spatial configurations across those processing pathways. These findings provide a detailed map of the diverse contribution of heritability and individual experience to the strength and topography of functional brain architecture.

YNIMG Journal 2022 Journal Article

Gradients in brain organization

• Boris C. Bernhardt
• Jonathan Smallwood
• Shella Keilholz
• Daniel S. Margulies

YNIMG Journal 2021 Journal Article

A collaborative resource platform for non-human primate neuroimaging

• Adam Messinger
• Nikoloz Sirmpilatze
• Katja Heuer
• Kep Kee Loh
• Rogier B. Mars
• Julien Sein
• Ting Xu
• Daniel Glen

Neuroimaging non-human primates (NHPs) is a growing, yet highly specialized field of neuroscience. Resources that were primarily developed for human neuroimaging often need to be significantly adapted for use with NHPs or other animals, which has led to an abundance of custom, in-house solutions. In recent years, the global NHP neuroimaging community has made significant efforts to transform the field towards more open and collaborative practices. Here we present the PRIMatE Resource Exchange (PRIME-RE), a new collaborative online platform for NHP neuroimaging. PRIME-RE is a dynamic community-driven hub for the exchange of practical knowledge, specialized analytical tools, and open data repositories, specifically related to NHP neuroimaging. PRIME-RE caters to both researchers and developers who are either new to the field, looking to stay abreast of the latest developments, or seeking to collaboratively advance the field .

YNIMG Journal 2021 Journal Article

Imaging evolution of the primate brain: the next frontier?

• Patrick Friedrich
• Stephanie J. Forkel
• Céline Amiez
• Joshua H. Balsters
• Olivier Coulon
• Lingzhong Fan
• Alexandros Goulas
• Fadila Hadj-Bouziane

Evolution, as we currently understand it, strikes a delicate balance between animals' ancestral history and adaptations to their current niche. Similarities between species are generally considered inherited from a common ancestor whereas observed differences are considered as more recent evolution. Hence comparing species can provide insights into the evolutionary history. Comparative neuroimaging has recently emerged as a novel subdiscipline, which uses magnetic resonance imaging (MRI) to identify similarities and differences in brain structure and function across species. Whereas invasive histological and molecular techniques are superior in spatial resolution, they are laborious, post-mortem, and oftentimes limited to specific species. Neuroimaging, by comparison, has the advantages of being applicable across species and allows for fast, whole-brain, repeatable, and multi-modal measurements of the structure and function in living brains and post-mortem tissue. In this review, we summarise the current state of the art in comparative anatomy and function of the brain and gather together the main scientific questions to be explored in the future of the fascinating new field of brain evolution derived from comparative neuroimaging.

YNIMG Journal 2021 Journal Article

Signal diffusion along connectome gradients and inter-hub routing differentially contribute to dynamic human brain function

• Bo-yong Park
• Reinder Vos de Wael
• Casey Paquola
• Sara Larivière
• Oualid Benkarim
• Jessica Royer
• Shahin Tavakol
• Raul R. Cruces

Human cognition is dynamic, alternating over time between externally-focused states and more abstract, often self-generated, patterns of thought. Although cognitive neuroscience has documented how networks anchor particular modes of brain function, mechanisms that describe transitions between distinct functional states remain poorly understood. Here, we examined how time-varying changes in brain function emerge within the constraints imposed by macroscale structural network organization. Studying a large cohort of healthy adults (n = 326), we capitalized on manifold learning techniques that identify low dimensional representations of structural connectome organization and we decomposed neurophysiological activity into distinct functional states and their transition patterns using Hidden Markov Models. Structural connectome organization predicted dynamic transitions anchored in sensorimotor systems and those between sensorimotor and transmodal states. Connectome topology analyses revealed that transitions involving sensorimotor states traversed short and intermediary distances and adhered strongly to communication mechanisms of network diffusion. Conversely, transitions between transmodal states involved spatially distributed hubs and increasingly engaged long-range routing. These findings establish that the structure of the cortex is optimized to allow neural states the freedom to vary between distinct modes of processing, and so provides a key insight into the neural mechanisms that give rise to the flexibility of human cognition.

YNIMG Journal 2020 Journal Article

A gradient from long-term memory to novel cognition: Transitions through default mode and executive cortex

• Xiuyi Wang
• Daniel S. Margulies
• Jonathan Smallwood
• Elizabeth Jefferies

Human cognition flexibly guides decision-making in familiar and novel situations. Although these decisions are often treated as dichotomous, in reality, situations are neither completely familiar, nor entirely new. Contemporary accounts of brain organization suggest that neural function is organized along a connectivity gradient from unimodal regions of sensorimotor cortex, through executive regions to transmodal default mode network. We examined whether this graded view of neural organization helps to explain how decision-making changes across situations that vary in their alignment with long-term knowledge. We used a semantic judgment task, which parametrically varied the global semantic similarity of items within a feature matching task to create a 'task gradient', from conceptual combinations that were highly overlapping in long-term memory to trials that only shared the goal-relevant feature. We found the brain's response to the task gradient varied systematically along the connectivity gradient, with the strongest response in default mode network when the probe and target items were highly overlapping conceptually. This graded functional change was seen in multiple brain regions and within individual brains, and was not readily explained by task difficulty. Moreover, the gradient captured the spatial layout of networks involved in semantic processing, providing an organizational principle for controlled semantic cognition across the cortex. In this way, the cortex is organized to support semantic decision-making in both highly familiar and less familiar situations.

YNIMG Journal 2020 Journal Article

Cross-species functional alignment reveals evolutionary hierarchy within the connectome

• Ting Xu
• Karl-Heinz Nenning
• Ernst Schwartz
• Seok-Jun Hong
• Joshua T. Vogelstein
• Alexandros Goulas
• Damien A. Fair
• Charles E. Schroeder

Evolution provides an important window into how cortical organization shapes function and vice versa. The complex mosaic of changes in brain morphology and functional organization that have shaped the mammalian cortex during evolution, complicates attempts to chart cortical differences across species. It limits our ability to fully appreciate how evolution has shaped our brain, especially in systems associated with unique human cognitive capabilities that lack anatomical homologues in other species. Here, we develop a function-based method for cross-species alignment that enables the quantification of homologous regions between humans and rhesus macaques, even when their location is decoupled from anatomical landmarks. Critically, we find cross-species similarity in functional organization reflects a gradient of evolutionary change that decreases from unimodal systems and culminates with the most pronounced changes in posterior regions of the default mode network (angular gyrus, posterior cingulate and middle temporal cortices). Our findings suggest that the establishment of the default mode network, as the apex of a cognitive hierarchy, has changed in a complex manner during human evolution - even within subnetworks.

YNIMG Journal 2020 Journal Article

Joint embedding: A scalable alignment to compare individuals in a connectivity space

• Karl-Heinz Nenning
• Ting Xu
• Ernst Schwartz
• Jesus Arroyo
• Adelheid Woehrer
• Alexandre R. Franco
• Joshua T. Vogelstein
• Daniel S. Margulies

A common coordinate space enabling comparison across individuals is vital to understanding human brain organization and individual differences. By leveraging dimensionality reduction algorithms, high-dimensional fMRI data can be represented in a low-dimensional space to characterize individual features. Such a representative space encodes the functional architecture of individuals and enables the observation of functional changes across time. However, determining comparable functional features across individuals in resting-state fMRI in a way that simultaneously preserves individual-specific connectivity structure can be challenging. In this work we propose scalable joint embedding to simultaneously embed multiple individual brain connectomes within a common space that allows individual representations across datasets to be aligned. Using Human Connectome Project data, we evaluated the joint embedding approach by comparing it to the previously established orthonormal alignment model. Alignment using joint embedding substantially increased the similarity of functional representations across individuals while simultaneously capturing their distinct profiles, allowing individuals to be more discriminable from each other. Additionally, we demonstrated that the common space established using resting-state fMRI provides a better overlap of task-activation across participants. Finally, in a more challenging scenario - alignment across a lifespan cohort aged from 6 to 85 - joint embedding provided a better prediction of age (r2 = 0. 65) than the prior alignment model. It facilitated the characterization of functional trajectories across lifespan. Overall, these analyses establish that joint embedding can simultaneously capture individual neural representations in a common connectivity space aligning functional data across participants and populations and preserve individual specificity.

YNIMG Journal 2020 Journal Article

Toward a connectivity gradient-based framework for reproducible biomarker discovery

• Seok-Jun Hong
• Ting Xu
• Aki Nikolaidis
• Jonathan Smallwood
• Daniel S. Margulies
• Boris Bernhardt
• Joshua Vogelstein
• Michael P. Milham

Despite myriad demonstrations of feasibility, the high dimensionality of fMRI data remains a critical barrier to its utility for reproducible biomarker discovery. Recent efforts to address this challenge have capitalized on dimensionality reduction techniques applied to resting-state fMRI, identifying principal components of intrinsic connectivity which describe smooth transitions across different cortical systems, so called “connectivity gradients”. These gradients recapitulate neurocognitively meaningful organizational principles that are present in both human and primate brains, and also appear to differ among individuals and clinical populations. Here, we provide a critical assessment of the suitability of connectivity gradients for biomarker discovery. Using the Human Connectome Project (discovery subsample=209; two replication subsamples= 209 × 2) and the Midnight scan club (n = 9), we tested the following key biomarker traits – reliability, reproducibility and predictive validity – of functional gradients. In doing so, we systematically assessed the effects of three analytical settings, including i) dimensionality reduction algorithms (i. e. , linear vs. non-linear methods), ii) input data types (i. e. , raw time series, [un-]thresholded functional connectivity), and iii) amount of the data (resting-state fMRI time-series lengths). We found that the reproducibility of functional gradients across algorithms and subsamples is generally higher for those explaining more variances of whole-brain connectivity data, as well as those having higher reliability. Notably, among different analytical settings, a linear dimensionality reduction (principal component analysis in our study), more conservatively thresholded functional connectivity (e. g. , 95–97%) and longer time-series data (at least ≥20mins) was found to be preferential conditions to obtain higher reliability. Those gradients with higher reliability were able to predict unseen phenotypic scores with a higher accuracy, highlighting reliability as a critical prerequisite for validity. Importantly, prediction accuracy with connectivity gradients exceeded that observed with more traditional edge-based connectivity measures, suggesting the added value of a low-dimensional and multivariate gradient approach. Finally, the present work highlights the importance and benefits of systematically exploring the parameter space for new imaging methods before widespread deployment.

YNIMG Journal 2019 Journal Article

Modes of operation: A topographic neural gradient supporting stimulus dependent and independent cognition

• Charlotte Murphy
• Hao-Ting Wang
• Delali Konu
• Rebecca Lowndes
• Daniel S. Margulies
• Elizabeth Jefferies
• Jonathan Smallwood

Human cognition is flexible - drawing on both sensory input, and representations from memory, to successfully navigate complex environments. Contemporary accounts suggest this flexibility is possible because neural function is organized into a hierarchy. Neural regions are organized along a macroscale gradient, anchored at one end by unimodal systems involved with perception and action, and at the other by transmodal systems, including the default mode network, supporting cognition less directly tied to immediate stimulus input. The current study tested whether this cortical hierarchy captures modes of behaviour that depend on immediate input, as well as those that depend on representations from memory. Participants made decisions regarding the location or identity of shapes using information in the environment (0-back) or from a prior trial (1-back). Using task based imaging we established that, regardless of the nature of the decision, medial and lateral visual cortex were recruited when decisions rely on immediate input, while transmodal regions were recruited when judgments depend on information from the prior trial. Using principal components analysis, we demonstrated that shifting decision-making from perception to memory altered the focus of neural activity from unimodal to transmodal regions (and vice versa). Notably, the more pronounced these shifts in neural activity from unimodal to transmodal regions when decisions relied on memory, the more efficiently individuals performed this task. These data illustrate how the macroscale organization of neural function into a hierarchy allows cognition to rely on input, or information from memory, in a flexible and efficient manner.

YNIMG Journal 2019 Journal Article

The ebb and flow of attention: Between-subject variation in intrinsic connectivity and cognition associated with the dynamics of ongoing experience

• Adam Turnbull
• Hao-Ting Wang
• Jonathan W. Schooler
• Elizabeth Jefferies
• Daniel S. Margulies
• Jonathan Smallwood

Cognition is dynamic, allowing us the flexibility to shift focus from different aspects of the environment, or between internally- and externally-oriented trains of thought. Although we understand how individuals switch attention across different tasks, the neurocognitive processes that underpin the dynamics of less constrained elements of cognition are less well understood. To explore this issue, we developed a paradigm in which participants intermittently responded to external events across two conditions that systematically vary in their need for updating working memory based on information in the external environment. This paradigm distinguishes the influences on cognition that emerge because of demands placed by the task (sustained) from changes that result from the time elapsed since the last task response (transient). We used experience sampling to identify dynamic changes in ongoing cognition in this paradigm, and related between subject variation in these measures to variations in the intrinsic organisation of large-scale brain networks. We found systems important for attention were involved in the regulation of off-task thought. Coupling between the ventral attention network and regions of primary motor cortex was stronger for individuals who were able to regulate off-task thought in line with the demands of the task. This pattern of coupling was linked to greater task-related thought when environmental demands were high and elevated off-task thought when demands were low. In contrast, the coupling of the dorsal attention network with a region of lateral visual cortex was stronger for individuals for whom off-task thoughts transiently increased with the time since responding to the external world. This pattern is consistent with a role for this system in the time-limited top-down biasing of visual processing to increase behavioural efficiency. Unlike the attention networks, coupling between regions of the default mode network and dorsal occipital cortex was weaker for individuals for whom the level of detail decreased with the passage of time when the external task did not require continuous monitoring of external information. These data provide novel evidence for how neural systems vary across subjects and may underpin individual variation in the dynamics of thought, linking attention systems to the maintenance of task-relevant information, and the default mode network to supporting experiences with vivid detail.

YNICL Journal 2019 Journal Article

The impact of ischemic stroke on connectivity gradients

• Şeyma Bayrak
• Ahmed A. Khalil
• Kersten Villringer
• Jochen B. Fiebach
• Arno Villringer
• Daniel S. Margulies
• Smadar Ovadia-Caro

The functional organization of the brain can be represented as a low-dimensional space that reflects its macroscale hierarchy. The dimensions of this space, described as connectivity gradients, capture the similarity of areas' connections along a continuous space. Studying how pathological perturbations with known effects on functional connectivity affect these connectivity gradients provides support for their biological relevance. Previous work has shown that localized lesions cause widespread functional connectivity alterations in structurally intact areas, affecting a network of interconnected regions. By using acute stroke as a model of the effects of focal lesions on the connectome, we apply the connectivity gradient framework to depict how functional reorganization occurs throughout the brain, unrestricted by traditional definitions of functional network boundaries. We define a three-dimensional connectivity space template based on functional connectivity data from healthy controls. By projecting lesion locations into this space, we demonstrate that ischemic strokes result in dimension-specific alterations in functional connectivity over the first week after symptom onset. Specifically, changes in functional connectivity were captured along connectivity Gradients 1 and 3. The degree of functional connectivity change was associated with the distance from the lesion along these connectivity gradients (a measure of functional similarity) regardless of the anatomical distance from the lesion. Together, these results provide support for the biological validity of connectivity gradients and suggest a novel framework to characterize connectivity alterations after stroke.

YNIMG Journal 2018 Journal Article

Automated individual-level parcellation of Broca's region based on functional connectivity

• Estrid Jakobsen
• Franziskus Liem
• Manousos A. Klados
• Şeyma Bayrak
• Michael Petrides
• Daniel S. Margulies

Broca's region can be subdivided into its constituent areas 44 and 45 based on established differences in connectivity to superior temporal and inferior parietal regions. The current study builds on our previous work manually parcellating Broca's area on the individual-level by applying these anatomical criteria to functional connectivity data. Here we present an automated observer-independent and anatomy-informed parcellation pipeline with comparable precision to the manual labels at the individual-level. The method first extracts individualized connectivity templates of areas 44 and 45 by assigning to each surface vertex within the ventrolateral frontal cortex the partial correlation value of its functional connectivity to group-level templates of areas 44 and 45, accounting for other template connectivity patterns. To account for cross-subject variability in connectivity, the partial correlation procedure is then repeated using individual-level network templates, including individual-level connectivity from areas 44 and 45. Each node is finally labeled as area 44, 45, or neither, using a winner-take-all approach. The method also incorporates prior knowledge of anatomical location by weighting the results using spatial probability maps. The resulting area labels show a high degree of spatial overlap with the gold-standard manual labels, and group-average area maps are consistent with cytoarchitectonic probability maps of areas 44 and 45. To facilitate reproducibility and to demonstrate that the method can be applied to resting-state fMRI datasets with varying acquisition and preprocessing parameters, the labeling procedure is applied to two open-source datasets from the Human Connectome Project and the Nathan Kline Institute Rockland Sample. While the current study focuses on Broca's region, the method is adaptable to parcellate other cortical regions with distinct connectivity profiles.

YNIMG Journal 2018 Journal Article

Distant from input: Evidence of regions within the default mode network supporting perceptually-decoupled and conceptually-guided cognition

• Charlotte Murphy
• Elizabeth Jefferies
• Shirley-Ann Rueschemeyer
• Mladen Sormaz
• Hao-Ting Wang
• Daniel S. Margulies
• Jonathan Smallwood

The default mode network supports a variety of mental operations such as semantic processing, episodic memory retrieval, mental time travel and mind-wandering, yet the commonalities between these functions remains unclear. One possibility is that this system supports cognition that is independent of the immediate environment; alternatively or additionally, it might support higher-order conceptual representations that draw together multiple features. We tested these accounts using a novel paradigm that separately manipulated the availability of perceptual information to guide decision-making and the representational complexity of this information. Using task based imaging we established regions that respond when cognition combines both stimulus independence with multi-modal information. These included left and right angular gyri and the left middle temporal gyrus. Although these sites were within the default mode network, they showed a stronger response to demanding memory judgements than to an easier perceptual task, contrary to the view that they support automatic aspects of cognition. In a subsequent analysis, we showed that these regions were located at the extreme end of a macroscale gradient, which describes gradual transitions from sensorimotor to transmodal cortex. This shift in the focus of neural activity towards transmodal, default mode, regions might reflect a process of where the functional distance from specific sensory enables conceptually rich and detailed cognitive states to be generated in the absence of input.

YNIMG Journal 2018 Journal Article

Trade-off of cerebello-cortical and cortico-cortical functional networks for planning in 6-year-old children

• Judy A. Kipping
• Daniel S. Margulies
• Simon B. Eickhoff
• Annie Lee
• Anqi Qiu

Childhood is a critical period for the development of cognitive planning. There is a lack of knowledge on its neural mechanisms in children. This study aimed to examine cerebello-cortical and cortico-cortical functional connectivity in association with planning skills in 6-year-olds (n = 76). We identified the cerebello-cortical and cortico-cortical functional networks related to cognitive planning using activation likelihood estimation (ALE) meta-analysis on existing functional imaging studies on spatial planning, and data-driven independent component analysis (ICA) of children's resting-state functional MRI (rs-fMRI). We investigated associations of cerebello-cortical and cortico-cortical functional connectivity with planning ability in 6-year-olds, as assessed using the Stockings of Cambridge task. Long-range functional connectivity of two cerebellar networks (lobules VI and lateral VIIa) with the prefrontal and premotor cortex were greater in children with poorer planning ability. In contrast, cortico-cortical association networks were not associated with the performance of planning in children. These results highlighted the key contribution of the lateral cerebello-frontal functional connectivity, but not cortico-cortical association functional connectivity, for planning ability in 6-year-olds. Our results suggested that brain adaptation to the acquisition of planning ability during childhood is partially achieved through the engagement of the cerebello-cortical functional connectivity.

YNIMG Journal 2017 Journal Article

In need of constraint: Understanding the role of the cingulate cortex in the impulsive mind

• Johannes Golchert
• Jonathan Smallwood
• Elizabeth Jefferies
• Franziskus Liem
• Julia M. Huntenburg
• Marcel Falkiewicz
• Mark E. Lauckner
• Sabine Oligschläger

Impulsive behavior often occurs without forethought and can be driven by strong emotions or sudden impulses, leading to problems in cognition and behavior across a wide range of situations. Although neuroimaging studies have explored the neurocognitive indicators of impulsivity, the large-scale functional networks that contribute to different aspects of impulsive cognition remain unclear. In particular, we lack a coherent account of why impulsivity is associated with such a broad range of different psychological features. Here, we use resting state functional connectivity, acquired in two independent samples, to investigate the neural substrates underlying different aspects of self-reported impulsivity. Based on the involvement of the anterior cingulate cortex (ACC) in cognitive but also affective processes, five seed regions were placed along the caudal to rostral gradient of the ACC. We found that positive urgency was related to functional connectivity between subgenual ACC and bilateral parietal regions such as retrosplenial cortex potentially highlighting this connection as being important in the modulation of the non-prospective, hastiness – related aspects of impulsivity. Further, two impulsivity dimensions were associated with significant alterations in functional connectivity of the supragenual ACC: (i) lack of perseverance was positively correlated to connectivity with the bilateral dorsolateral prefrontal cortex and right inferior frontal gyrus and (ii) lack of premeditation was inversely associated with functional connectivity with clusters within bilateral occipital cortex. Further analysis revealed that these connectivity patterns overlapped with bilateral dorsolateral prefrontal and bilateral occipital regions of the multiple demand network, a large-scale neural system implicated in the general control of thought and action. Together these results demonstrate that different forms of impulsivity have different neural correlates, which are linked to the functional connectivity of a region of anterior cingulate cortex. This suggests that poor perseveration and premeditation might be linked to dysfunctions in how the rostral zone of the ACC interacts with the multiple demand network that allows cognition to proceed in a controlled way.

YNIMG Journal 2017 Journal Article

Individual variation in intentionality in the mind-wandering state is reflected in the integration of the default-mode, fronto-parietal, and limbic networks

• Johannes Golchert
• Jonathan Smallwood
• Elizabeth Jefferies
• Paul Seli
• Julia M. Huntenburg
• Franziskus Liem
• Mark E. Lauckner
• Sabine Oligschläger

Mind-wandering has a controversial relationship with cognitive control. Existing psychological evidence supports the hypothesis that episodes of mind-wandering reflect a failure to constrain thinking to task-relevant material, as well the apparently alternative view that control can facilitate the expression of self-generated mental content. We assessed whether this apparent contradiction arises because of a failure to consider differences in the types of thoughts that occur during mind-wandering, and in particular, the associated level of intentionality. Using multi-modal magnetic resonance imaging (MRI) analysis, we examined the cortical organisation that underlies inter-individual differences in descriptions of the spontaneous or deliberate nature of mind-wandering. Cortical thickness, as well as functional connectivity analyses, implicated regions relevant to cognitive control and regions of the default-mode network for individuals who reported high rates of deliberate mind-wandering. In contrast, higher reports of spontaneous mind-wandering were associated with cortical thinning in parietal and posterior temporal regions in the left hemisphere (which are important in the control of cognition and attention) as well as heightened connectivity between the intraparietal sulcus and a region that spanned limbic and default-mode regions in the ventral inferior frontal gyrus. Finally, we observed a dissociation in the thickness of the retrosplenial cortex/lingual gyrus, with higher reports of spontaneous mind-wandering being associated with thickening in the left hemisphere, and higher repots of deliberate mind-wandering with thinning in the right hemisphere. These results suggest that the intentionality of the mind-wandering state depends on integration between the control and default-mode networks, with more deliberation being associated with greater integration between these systems. We conclude that one reason why mind-wandering has a controversial relationship with control is because it depends on whether the thoughts emerge in a deliberate or spontaneous fashion.

YNIMG Journal 2017 Journal Article

Predicting brain-age from multimodal imaging data captures cognitive impairment

• Franziskus Liem
• Gaël Varoquaux
• Jana Kynast
• Frauke Beyer
• Shahrzad Kharabian Masouleh
• Julia M. Huntenburg
• Leonie Lampe
• Mehdi Rahim

The disparity between the chronological age of an individual and their brain-age measured based on biological information has the potential to offer clinically relevant biomarkers of neurological syndromes that emerge late in the lifespan. While prior brain-age prediction studies have relied exclusively on either structural or functional brain data, here we investigate how multimodal brain-imaging data improves age prediction. Using cortical anatomy and whole-brain functional connectivity on a large adult lifespan sample (N=2354, age 19–82), we found that multimodal data improves brain-based age prediction, resulting in a mean absolute prediction error of 4. 29 years. Furthermore, we found that the discrepancy between predicted age and chronological age captures cognitive impairment. Importantly, the brain-age measure was robust to confounding effects: head motion did not drive brain-based age prediction and our models generalized reasonably to an independent dataset acquired at a different site (N=475). Generalization performance was increased by training models on a larger and more heterogeneous dataset. The robustness of multimodal brain-age prediction to confounds, generalizability across sites, and sensitivity to clinically-relevant impairments, suggests promising future application to the early prediction of neurocognitive disorders.

YNIMG Journal 2017 Journal Article

The Neuro Bureau ADHD-200 Preprocessed repository

• Pierre Bellec
• Carlton Chu
• François Chouinard-Decorte
• Yassine Benhajali
• Daniel S. Margulies
• R. Cameron Craddock

In 2011, the “ADHD-200 Global Competition” was held with the aim of identifying biomarkers of attention-deficit/hyperactivity disorder from resting-state functional magnetic resonance imaging (rs-fMRI) and structural MRI (s-MRI) data collected on 973 individuals. Statisticians and computer scientists were potentially the most qualified for the machine learning aspect of the competition, but generally lacked the specialized skills to implement the necessary steps of data preparation for rs-fMRI. Realizing this barrier to entry, the Neuro Bureau prospectively collaborated with all competitors by preprocessing the data and sharing these results at the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) (http: //www. nitrc. org/frs/? group_id=383). This “ADHD-200 Preprocessed” release included multiple analytical pipelines to cater to different philosophies of data analysis. The processed derivatives included denoised and registered 4D fMRI volumes, regional time series extracted from brain parcellations, maps of 10 intrinsic connectivity networks, fractional amplitude of low frequency fluctuation, and regional homogeneity, along with grey matter density maps. The data was used by several teams who competed in the ADHD-200 Global Competition, including the winning entry by a group of biostaticians. To the best of our knowledge, the ADHD-200 Preprocessed release was the first large public resource of preprocessed resting-state fMRI and structural MRI data, and remains to this day the only resource featuring a battery of alternative processing paths.

YNIMG Journal 2016 Journal Article

Longitudinal changes in resting-state fMRI from age 5 to age 6 years covary with language development

• Yaqiong Xiao
• Angela D. Friederici
• Daniel S. Margulies
• Jens Brauer

Resting-state functional magnetic resonance imaging is a powerful technique to study the whole-brain neural connectivity that underlies cognitive systems. The present study aimed to define the changes in neural connectivity in their relation to language development. Longitudinal resting-state functional data were acquired from a cohort of preschool children at age 5 and one year later, and changes in functional connectivity were correlated with language performance in sentence comprehension. For this, degree centrality, a voxel-based network measure, was used to assess age-related differences in connectivity at the whole-brain level. Increases in connectivity with age were found selectively in a cluster within the left posterior superior temporal gyrus and sulcus (STG/STS). In order to further specify the connection changes, a secondary seed-based functional connectivity analysis on this very cluster was performed. The correlations between resting-state functional connectivity (RSFC) and language performance revealed developmental effects with age and, importantly, also dependent on the advancement in sentence comprehension ability over time. In children with greater advancement in language abilities, the behavioral improvement was positively correlated with RSFC increase between left posterior STG/STS and other regions of the language network, i. e. , left and right inferior frontal cortex. The age-related changes observed in this study provide evidence for alterations in the language network as language develops and demonstrates the viability of this approach for the investigation of normal and aberrant language development.

YNIMG Journal 2016 Journal Article

NeuroVault.org: A repository for sharing unthresholded statistical maps, parcellations, and atlases of the human brain

• Krzysztof J. Gorgolewski
• Gael Varoquaux
• Gabriel Rivera
• Yannick Schwartz
• Vanessa V. Sochat
• Satrajit S. Ghosh
• Camille Maumet
• Thomas E. Nichols

NeuroVault. org is dedicated to storing outputs of analyses in the form of statistical maps, parcellations and atlases, a unique strategy that contrasts with most neuroimaging repositories that store raw acquisition data or stereotaxic coordinates. Such maps are indispensable for performing meta-analyses, validating novel methodology, and deciding on precise outlines for regions of interest (ROIs). NeuroVault is open to maps derived from both healthy and clinical populations, as well as from various imaging modalities (sMRI, fMRI, EEG, MEG, PET, etc.). The repository uses modern web technologies such as interactive web-based visualization, cognitive decoding, and comparison with other maps to provide researchers with efficient, intuitive tools to improve the understanding of their results. Each dataset and map is assigned a permanent Universal Resource Locator (URL), and all of the data is accessible through a REST Application Programming Interface (API). Additionally, the repository supports the NIDM-Results standard and has the ability to parse outputs from popular FSL and SPM software packages to automatically extract relevant metadata. This ease of use, modern web-integration, and pioneering functionality holds promise to improve the workflow for making inferences about and sharing whole-brain statistical maps.

YNIMG Journal 2014 Journal Article

Common intrinsic connectivity states among posteromedial cortex subdivisions: Insights from analysis of temporal dynamics

• Zhen Yang
• R. Cameron Craddock
• Daniel S. Margulies
• Chao-Gan Yan
• Michael P. Milham

Perspectives of human brain functional connectivity continue to evolve. Static representations of functional interactions between brain regions are rapidly giving way to dynamic perspectives, which emphasize non-random temporal variations in intrinsic functional connectivity (iFC) patterns. Here, we bring this dynamic perspective to our understanding of iFC patterns for posteromedial cortex (PMC), a cortical hub known for its functional diversity. Previous work has consistently differentiated iFC patterns among PMC subregions, though assumed static iFC over time. Here, we assessed iFC as a function of time utilizing a sliding-window correlation approach, and applied hierarchical clustering to detect representative iFC states from the windowed iFC. Across subregions, five iFC states were detected over time. Although with differing frequencies, each subregion was associated with each of the states, suggesting that these iFC states are “common” to PMC subregions. Importantly, each subregion possessed a unique preferred state(s) and distinct transition patterns, explaining previously observed iFC differentiations. These results resonate with task-based fMRI studies suggesting that large-scale functional networks can be flexibly reconfigured in response to changing task-demands. Additionally, we used retest scans (~1week later) to demonstrate the reproducibility of the iFC states identified, and establish moderate to high test–retest reliability for various metrics used to quantify switching behaviors. We also demonstrate the ability of dynamic properties in the visual PMC subregion to index inter-individual differences in a measure of concept formation and mental flexibility. These findings suggest functional relevance of dynamic iFC and its potential utility in biomarker identification over time, as d-iFC methodologies are refined and mature.

YNIMG Journal 2013 Journal Article

Overlapping and parallel cerebello-cerebral networks contributing to sensorimotor control: An intrinsic functional connectivity study

• Judy A. Kipping
• Wolfgang Grodd
• Vinod Kumar
• Marco Taubert
• Arno Villringer
• Daniel S. Margulies

In concert with sensorimotor control areas of the cerebrum, the cerebellum shows differential activation patterns during a variety of sensorimotor-related tasks. However, the spatial details and extent of the complex and heterogeneous cerebello-cerebral systems involved in action control remain uncertain. In this study, we use intrinsic functional connectivity (iFC) to examine cerebello-cerebral networks of five cerebellar lobules (I–IV, V, VI, and VIIIa/b) that have been empirically identified to form the functional basis of sensorimotor processes. A refined cerebellar seed-region selection allowed us to identify a network of primary sensorimotor and supplementary motor areas (I–V), a network of prefrontal, premotor, occipito-temporal and inferior-parietal regions (VI), and two largely overlapping networks involving premotor and superior parietal regions, the temporo-parietal junction as well as occipito-temporal regions (VIIIa/b). All networks involved the medial prefrontal/cingulate cortex. These cerebral clusters were used in a partial correlation analysis to systematically map cerebral connectivity throughout the entire cerebellum. We discuss these findings in the framework of affective and cognitive control, sensorimotor, multisensory systems, and executive/language systems. Within the cerebellum we found that cerebro-cerebellar systems seem to run in parallel, as indicated by distinct sublobular functional topography of prefrontal, parietal, sensorimotor, cingulate, and occipito-temporal regions. However, all areas showed overlapping connectivity to various degrees in both hemispheres. The results of both analyses demonstrate that different sublobular parts of the cerebellar lobules may dominate in different aspects of primary or higher-order sensorimotor processing. This systems-level cerebellar organization provides a more detailed structure for cerebello-cerebral interaction which contributes to our understanding of complex motor behavior.

YNIMG Journal 2013 Journal Article

Visualizing the human connectome

• Daniel S. Margulies
• Joachim Böttger
• Aimi Watanabe
• Krzysztof J. Gorgolewski

Innovations in data visualization punctuate the landmark advances in human connectome research since its beginnings. From tensor glyphs for diffusion-weighted imaging, to advanced rendering of anatomical tracts, to more recent graph-based representations of functional connectivity data, many of the ways we have come to understand the human connectome are through the intuitive insight these visualizations enable. Nonetheless, several unresolved problems persist. For example, probabilistic tractography lacks the visual appeal of its deterministic equivalent, multimodal representations require extreme levels of data reduction, and rendering the full connectome within an anatomical space makes the contents cluttered and unreadable. In part, these challenges require compromises between several tensions that determine connectome visualization practice, such as prioritizing anatomic or connectomic information, aesthetic appeal or information content, and thoroughness or readability. To illustrate the ongoing negotiation between these priorities, we provide an overview of various visualization methods that have evolved for anatomical and functional connectivity data. We then describe interactive visualization tools currently available for use in research, and we conclude with concerns and developments in the presentation of connectivity results.

YNIMG Journal 2011 Journal Article

Long-term effects of motor training on resting-state networks and underlying brain structure

• Marco Taubert
• Gabriele Lohmann
• Daniel S. Margulies
• Arno Villringer
• Patrick Ragert

Acquired motor skills are coded in fronto-parietal brain networks, but how these networks evolve through motor training is unclear. On the one hand, increased functional connectivity has been shown immediately after a training session; on the other hand, training-induced structural changes are visible only after several weeks. Based on known associations between functional and structural network development during human ontogeny, we hypothesised that learning a challenging motor task leads to long-lasting changes in functional resting-state networks and the corresponding cortical and sub-cortical brain structures. Using longitudinal functional and structural MRI at multiple time points, we demonstrate increased fronto-parietal network connectivity one week after two brief motor training sessions in a dynamic balancing task, although subjects were engaged in their regular daily activities during the week. Repeated training sessions over six consecutive weeks progressively modulate these changes in accordance with individual performance improvements. Multimodal correlation analyses showed an association between structural grey matter alterations and functional connectivity changes in prefrontal and supplementary-motor areas. These coincident changes were most prominent in the first three weeks of training. In contrast, changes in fronto-parietal functional connectivity and the underlying white matter fibre structure developed gradually during the six weeks. Our results demonstrate a tight correlation between training-induced functional and structural brain plasticity on the systems level and suggest a functional relevance of intrinsic brain activity for morphological adaptation in the human brain.

YNIMG Journal 2011 Journal Article

Low frequency fluctuations reveal integrated and segregated processing among the cerebral hemispheres

• Dylan G. Gee
• Bharat B. Biswal
• Clare Kelly
• David E. Stark
• Daniel S. Margulies
• Zarrar Shehzad
• Lucina Q. Uddin
• Donald F. Klein

Resting-state functional magnetic resonance imaging (fMRI) has provided a novel approach for examining interhemispheric interaction, demonstrating a high degree of functional connectivity between homotopic regions in opposite hemispheres. However, heterotopic resting-state functional connectivity (RSFC) remains relatively uncharacterized. In the present study, we examine non-homotopic regions, characterizing heterotopic RSFC and comparing it to intrahemispheric RSFC, to examine the impact of hemispheric separation on the integration and segregation of processing in the brain. Resting-state fMRI scans were acquired from 59 healthy participants to examine inter-regional correlations in spontaneous low frequency fluctuations in BOLD signal. Using a probabilistic atlas, we correlated probability-weighted time series from 112 regions (56 per hemisphere) distributed throughout the entire cerebrum. We compared RSFC for pairings of non-homologous regions located in different hemispheres (heterotopic connectivity) to RSFC for the same pairings when located within hemisphere (intrahemispheric connectivity). For positive connections, connectivity strength was greater within each hemisphere, consistent with integrated intrahemispheric processing. However, for negative connections, RSFC strength was greater between the hemispheres, consistent with segregated interhemispheric processing. These patterns were particularly notable for connections involving frontal and heteromodal regions. The distribution of positive and negative connectivity was nearly identical within and between the hemispheres, though we demonstrated detailed regional variation in distribution. We discuss implications for leading models of interhemispheric interaction. The future application of our analyses may provide important insight into impaired interhemispheric processing in clinical and aging populations.

YNIMG Journal 2010 Journal Article

Delineating self-referential processing from episodic memory retrieval: Common and dissociable networks

• Bastian Sajonz
• Thorsten Kahnt
• Daniel S. Margulies
• Soyoung Q. Park
• André Wittmann
• Meline Stoy
• Andreas Ströhle
• Andreas Heinz

Self-referential processing involves a complex set of cognitive functions, posing challenges to delineating its independent neural correlates. While self-referential processing has been considered functionally intertwined with episodic memory, the present study explores their overlap and dissociability. Standard tasks for self-referential processing and episodic memory were combined into a single fMRI experiment. Contrasting the effects of self-relatedness and retrieval success allowed for the two processes to be delineated. Stimuli judged as self-referential specifically activated the posterior cingulate/anterior precuneus, the medial prefrontal cortex, and an inferior division of the inferior parietal lobule. In contrast, episodic memory retrieval specifically involved the posterior precuneus, the right anterior prefrontal cortex, and a superior division of the inferior parietal lobule (extending into superior parietal lobule). Overlapping activations were found in intermediate zones in the precuneus and the inferior parietal lobule, but not in the prefrontal cortex. While our data show common networks for both processes in the medial and lateral parietal cortex, three functional differentiations were also observed: (1) an anterior–posterior differentiation within the medial parietal cortex; (2) a medial–anterolateral differentiation within the prefrontal cortex; and, (3) an inferior–superior differentiation within the lateral parietal cortex for self-referential processing versus episodic memory retrieval.

YNIMG Journal 2009 Journal Article

Functional connectivity of the human amygdala using resting state fMRI

• Amy Krain Roy
• Zarrar Shehzad
• Daniel S. Margulies
• A.M. Clare Kelly
• Lucina Q. Uddin
• Kristin Gotimer
• Bharat B. Biswal
• F. Xavier Castellanos

The amygdala is composed of structurally and functionally distinct nuclei that contribute to the processing of emotion through interactions with other subcortical and cortical structures. While these circuits have been studied extensively in animals, human neuroimaging investigations of amygdala-based networks have typically considered the amygdala as a single structure, which likely masks contributions of individual amygdala subdivisions. The present study uses resting state functional magnetic resonance imaging (fMRI) to test whether distinct functional connectivity patterns, like those observed in animal studies, can be detected across three amygdala subdivisions: laterobasal, centromedial, and superficial. In a sample of 65 healthy adults, voxelwise regression analyses demonstrated positively-predicted ventral and negatively-predicted dorsal networks associated with the total amygdala, consistent with previous animal and human studies. Investigation of individual amygdala subdivisions revealed distinct differences in connectivity patterns within the amygdala and throughout the brain. Spontaneous activity in the laterobasal subdivision predicted activity in temporal and frontal regions, while activity in the centromedial nuclei predicted activity primarily in striatum. Activity in the superficial subdivision positively predicted activity throughout the limbic lobe. These findings suggest that resting state fMRI can be used to investigate human amygdala networks at a greater level of detail than previously appreciated, allowing for the further advancement of translational models.

YNIMG Journal 2007 Journal Article

Mapping the functional connectivity of anterior cingulate cortex

• Daniel S. Margulies
• A.M. Clare Kelly
• Lucina Q. Uddin
• Bharat B. Biswal
• F. Xavier Castellanos
• Michael P. Milham

Anterior cingulate cortex (ACC) is a nexus of information processing and regulation in the brain. Reflecting this central role, ACC is structurally and functionally heterogeneous, a fact long appreciated in studies of non-human primates. Human neuroimaging studies also recognize this functional heterogeneity, with meta-analyses and task-based studies demonstrating the existence of motor, cognitive and affective subdivisions. In contrast to task-based approaches, examinations of resting-state functional connectivity enable the characterization of task-independent patterns of correlated activity. In a novel approach to understanding ACC functional segregation, we systematically mapped ACC functional connectivity during rest. We examined patterns of functional connectivity for 16 seed ROIs systematically placed throughout caudal, rostral, and subgenual ACC in each hemisphere. First, our data support the commonly observed rostral/caudal distinction, but also suggest the existence of a dorsal/ventral functional distinction. For each of these distinctions, more fine-grained patterns of differentiation were observed than commonly appreciated in human imaging studies. Second, we demonstrate the presence of negatively predicted relationships between distinct ACC functional networks. In particular, we highlight negative relationships between rostral ACC-based affective networks (including the “default mode network”) and dorsal–caudal ACC-based frontoparietal attention networks. Finally, interhemispheric activations were more strongly correlated between homologous regions than in non-homologous regions. We discuss the implications of our work for understanding ACC function and potential applications to clinical populations.