B.T. Thomas Yeo

B.T. Thomas Yeo
National University of Singapore | NUS · Department of Electrical & Computer Engineering

PhD

About

151
Publications
49,564
Reads
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18,715
Citations
Additional affiliations
September 2011 - November 2013
Duke-NUS Medical School
Position
  • PostDoc Position
October 2009 - August 2011
Harvard University
Position
  • PostDoc Position
October 2009 - August 2011
Harvard University
Position
  • PostDoc Position

Publications

Publications (151)
Article
Full-text available
The association cortex supports cognitive functions enabling flexible behavior. Here, we explored the organization of human association cortex by mathematically formalizing the notion that a behavioral task engages multiple cognitive components, which are in turn supported by multiple overlapping brain regions. Application of the model to a large d...
Article
Full-text available
We used a data-driven Bayesian model to automatically identify distinct latent factors of overlapping atrophy patterns from voxel-wise structural MRIs of late-onset Alzheimer's disease (AD) dementia patients. Our approach estimated the extent to which multiple distinct atrophy patterns were expressed within each participant rather than assuming tha...
Article
Full-text available
A central goal in systems neuroscience is the parcellation of the cerebral cortex into discrete neurobiological "atoms". Resting-state functional magnetic resonance imaging (rs-fMRI) offers the possibility of in vivo human cortical parcellation. Almost all previous parcellations relied on 1 of 2 approaches. The local gradient approach detects abrup...
Article
Full-text available
Resting-state functional magnetic resonance imaging (rs-fMRI) offers the opportunity to delineate individual-specific brain networks. A major question is whether individual-specific network topography (i.e., location and spatial arrangement) is behaviorally relevant. Here, we propose a multi-session hierarchical Bayesian model (MS-HBM) for estimati...
Article
Full-text available
Resting-state functional connectivity is a powerful tool for studying human functional brain networks. Temporal fluctuations in functional connectivity, i.e., dynamic functional connectivity (dFC), are thought to reflect dynamic changes in brain organization and non-stationary switching of discrete brain states. However, recent studies have suggest...
Article
Full-text available
How individual differences in brain network organization track behavioral variability is a fundamental question in systems neuroscience. Recent work suggests that resting-state and task-state functional connectivity can predict specific traits at the individual level. However, most studies focus on single behavioral traits, thus not capturing broad...
Preprint
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In recent years, deep learning has unlocked unprecedented success in various domains, especially in image, text, and speech processing. These breakthroughs may hold promise for neuroscience and especially for brain-imaging investigators who start to analyze thousands of participants. However, deep learning is only beneficial if the data have nonlin...
Preprint
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There is significant interest in using brain imaging data to predict non-brain-imaging phenotypes in individual participants. However, most prediction studies are underpowered, relying on less than a few hundred participants, leading to low reliability and inflated prediction performance. Yet, small sample sizes are unavoidable when studying clinic...
Article
Objective To determine whether atrophy relates to phenotypical variants of posterior cortical atrophy (PCA) recently proposed in clinical criteria; dorsal, ventral, dominant-parietal and caudal, we assessed associations between latent atrophy factors and cognition. Methods We employed a data-driven Bayesian modelling framework based on latent Diri...
Article
COVER ILLUSTRATION Resting‐state functional magnetic resonance imaging (rs‐fMRI) is widely used to compare relevant features of the resting‐state brain between a clinically‐disordered and healthy‐control group. Thus, the rsfMRI of individuals in a healthy‐control group that constitutes the baseline of comparison plays a vital role in the appropriat...
Preprint
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Major depressive disorder emerges from the complex interactions of biological systems that span across genes and molecules through cells, circuits, networks, and behavior. Establishing how neurobiological processes coalesce to contribute to the onset and maintenance of depression requires a multi-scale approach, encompassing measures of brain struc...
Preprint
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Structural and functional characteristics of the cortex systematically vary along global axes as a function of cytoarchitecture, gene expression, and connectivity. The topology of the cerebral cortex has been proposed to be a prerequisite for the emergence of human cognition and explain both the impact and progression of pathology. However, the neu...
Preprint
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We present the findings of "The Alzheimer's Disease Prediction Of Longitudinal Evolution" (TADPOLE) Challenge, which compared the performance of 92 algorithms from 33 international teams at predicting the future trajectory of 219 individuals at risk of Alzheimer's disease. Challenge participants were required to make a prediction, for each month of...
Article
Attention is a critical cognitive function, allowing humans to select, enhance, and sustain focus on information of behavioral relevance. Attention contains dissociable neural and psychological components. Nevertheless, some brain networks support multiple attentional functions. In this study, we used the visual attentional blink (VAB) as a test of...
Article
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The impact of in-scanner motion on functional magnetic resonance imaging (fMRI) data has a notorious reputation in the neuroimaging community. State-of-the-art guidelines advise to scrub out excessively corrupted frames as assessed by a composite framewise displacement (FD) score, to regress out models of nuisance variables, and to include average...
Preprint
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There is a general consensus that substantial heterogeneity underlies the neurobiology in autism spectrum disorder (ASD). As such, it has become increasingly clear that a dissection of variation at the molecular-, cellular-, and system-level domains is a prerequisite for identifying biomarkers and developing more targeted therapeutic strategies in...
Article
Full-text available
Patterns in resting‐state fMRI (rs‐fMRI) are widely used to characterize the trait effects of brain function. In this aspect, multiple rs‐fMRI scans from single subjects can provide interesting clues about the rs‐fMRI patterns, though scan‐to‐scan variability pose challenges. Therefore, rs‐fMRI's are either concatenated or the functional connectivi...
Article
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The past decade has witnessed a proliferation of studies aimed at characterizing the human connectome. These projects map the brain regions comprising large-scale systems underlying cognition using non-invasive neuroimaging approaches and advanced analytic techniques adopted from network science. While the idea that the human brain is composed of m...
Article
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Background: Heterogeneity in autism spectrum disorder (ASD) has hindered the development of biomarkers, thus motivating subtyping efforts. Most subtyping studies divide individuals with ASD into nonoverlapping (categorical) subgroups. However, continuous interindividual variation in ASD suggests that there is a need for a dimensional approach. Me...
Article
Full-text available
A reliable set of functional brain networks is found in healthy people and thought to underlie our cognition, emotion, and behavior. Here, we investigated these networks by quantifying intrinsic functional connectivity in six individuals who had undergone surgical removal of one hemisphere. Hemispherectomy subjects and healthy controls were scanned...
Article
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The global signal in resting-state functional MRI data is considered to be dominated by physiological noise and artifacts, yet a growing literature suggests that it also carries information about widespread neural activity. The biological relevance of the global signal remains poorly understood. Applying principal component analysis to a large neur...
Article
Full-text available
There is significant interest in the development and application of deep neural networks (DNNs) to neuroimaging data. A growing literature suggests that DNNs outperform their classical counterparts in a variety of neuroimaging applications, yet there are few direct comparisons of relative utility. Here, we compared the performance of three DNN arch...
Preprint
Full-text available
Patterns in resting-state fMRI (rs-fMRI) are widely used to characterize the trait effects of brain function. In this aspect, multiple rs-fMRI scans from single subjects can provide interesting clues about the rs-fMRI patterns, though scan-to-scan variability pose challenges. Therefore, rs-fMRIs are either concatenated or the functional connectivit...
Preprint
Full-text available
Humans need about 7 to 9 hours of sleep per night. Sleep habits are heritable, associated with brain function and structure, and intrinsically related to well-being, mental and physical health. This raises the question whether associations between sleep, mental and physical health can be attributed to a shared macroscale neurobiology. Combining neu...
Preprint
Personality traits quantify individual differences in goals, cognition, and emotion, that lead to behavior. Evidence from psychology, cognitive neuroscience, and genetics has proposed links between personality and brain structure. In the current study, we used a twin-design to test whether covariance between personality and brain structure is due t...
Preprint
Full-text available
Early identification of individuals at risk of developing Alzheimer's disease (AD) dementia is important for developing disease-modifying therapies. In this study, given multimodal AD markers and clinical diagnosis of an individual from one or more timepoints, we seek to predict the clinical diagnosis, cognition and ventricular volume of the indivi...
Article
The field of digital therapeutics represents a gateway towards using artificial intelligence to optimize software‐based interventions. In article 1900023, Dean Ho, Christopher L. Asplund and co‐workers integrate CURATE.AI with the Multi‐Attribute Task Battery (MATB) platform in a prospective pilot study to identify N‐of‐1 profiles as foundations fo...
Preprint
Full-text available
Standard brain templates and growth charts provide an invaluable resource for basic science research, with the eventual goal of contributing to the clinical care of neuropsychiatric conditions. Here, we report on a protocol to generate MRI brain templates in children and adolescents at one-year intervals from 6-to-18 years of age, with their corres...
Preprint
Full-text available
Attention is a critical cognitive function, allowing humans to select, enhance, and sustain focus on information of behavioral relevance. Attention contains dissociable neural and psychological components. Nevertheless, some brain networks support multiple attentional functions. Connectome-based Predictive Models (CPM), which associate individual d...
Preprint
Full-text available
Background: Heterogeneity in autism spectrum disorder (ASD) has hindered the development of biomarkers, thus motivating subtyping efforts. Most subtyping studies divide ASD individuals into non-overlapping (categorical) subgroups. However, continuous inter-individual variation in ASD suggests the need for a dimensional approach. Methods: A Bayesian...
Article
Individuals with Alzheimer’s disease (AD) dementia exhibit significant heterogeneity across clinical symptoms, atrophy patterns, and spatial distribution of Tau deposition. Most previous studies of AD heterogeneity have focused on atypical clinical subtypes, defined subtypes with a single modality, or restricted their analyses to a priori brain reg...
Article
Full-text available
A large amount of brain imaging research has focused on group studies delineating differences between males and females with respect to both cognitive performance as well as structural and functional brain organization. To supplement existing findings, the present study employed a machine learning approach to assess how accurately participants' sex...
Preprint
Posterior cortical atrophy is a clinical-radiological syndrome characterized by visual processing deficits and atrophy in posterior parts of the brain, most often caused by Alzheimers disease pathology. Recent consensus criteria describe four distinct phenotypical variants of posterior cortical atrophy defined by clinical and radiological features;...
Preprint
There is great interest in elucidating the cluster structure of brain networks in terms of modules, blocks or clusters of similar nodes. However, it is currently challenging to handle data on multiple subjects since most of the existing methods are applicable only on a subject-by-subject basis or for analysis of a group average network. The main li...
Article
Coordinate-based meta-analysis can provide important insights into mind-brain relationships. A popular approach for curated small-scale meta-analysis is activation likelihood estimation (ALE), which identifies brain regions consistently activated across a selected set of experiments, such as within a functional domain or mental disorder. ALE can al...
Article
Full-text available
Background: There is considerable interest in a dimensional transdiagnostic approach to psychiatry. Most transdiagnostic studies have derived factors based only on clinical symptoms, which might miss possible links between psychopathology, cognitive processes, and personality traits. Furthermore, many psychiatric studies focus on higher-order asso...
Preprint
Full-text available
The brain exhibits substantial diurnal variation in physiology and function but neuroscience studies rarely report or consider the effects of time of day. Here, we examined variation in resting-state fMRI in around 900 subjects scanned between 8am to 10pm on two different days. Multiple studies across animals and humans have demonstrated that the b...
Article
Full-text available
Linking human behavior to resting-state brain function is a central question in systems neuroscience. In particular, the functional timescales at which different types of behavioral factors are encoded remain largely unexplored. The behavioral counterparts of static functional connectivity (FC), at the resolution of several minutes, have been studi...
Article
Conventional therapeutic interventions, which range from drug treatment to learning and training regimens, are often given at a fixed dose/intensity. This often leads to sub‐optimal responses, or even none at all. Similarly, fixed intensity training can lead to plateaus in learning trajectories and training outcomes. This barrier will impact the fi...
Preprint
Full-text available
Background: There is considerable interest in a dimensional transdiagnostic approach to psychiatry. Most transdiagnostic studies have derived factors based only on clinical symptoms, which might miss possible links between psychopathology, cognitive processes and personality traits. Furthermore, many psychiatric studies focus on higher-order associ...
Preprint
Full-text available
A large amount of brain imaging research has focused on group studies delineating differences between males and females with respect to both cognitive performance as well as structural and functional brain organization. To supplement existing findings, the present study employed a machine learning approach to assess how accurately participants' sex...
Article
There is significant interest in using resting-state functional connectivity (RSFC) to predict human behavior. Good behavioral prediction should in theory require RSFC to be sufficiently distinct across participants; if RSFC were the same across participants, then behavioral prediction would obviously be poor. Therefore, we hypothesize that removin...
Article
Global signal regression (GSR) is one of the most debated preprocessing strategies for resting-state functional MRI. GSR effectively removes global artifacts driven by motion and respiration, but also discards globally distributed neural information and introduces negative correlations between certain brain regions. The vast majority of previous st...
Article
Component analysis is a powerful tool to identify dominant patterns of interactions in multivariate datasets. In the context of fMRI data, methods such as principal component analysis or independent component analysis have been used to identify the brain networks shaping functional connectivity (FC). Importantly, these approaches are static in the...
Preprint
Full-text available
Global signal regression (GSR) is one of the most debated preprocessing strategies for resting-state functional MRI. GSR effectively removes global artifacts driven by motion and respiration, but also discards globally distributed neural information and introduces negative correlations between certain brain regions. The vast majority of previous st...
Preprint
Full-text available
There is significant interest in using resting-state functional connectivity (RSFC) to predict human behavior. Good behavioral prediction should in theory require RSFC to be sufficiently distinct across participants; if RSFC were the same across participants, then behavioral prediction would obviously be poor. Therefore, we hypothesize that removin...
Article
Full-text available
We considered a large-scale dynamical circuit model of human cerebral cortex with region-specific microscale properties. The model was inverted using a stochastic optimization approach, yielding markedly better fit to new, out-of-sample resting functional magnetic resonance imaging (fMRI) data. Without assuming the existence of a hierarchy, the est...
Preprint
Full-text available
There is significant interest in the development and application of deep neural networks (DNNs) to neuroimaging data. A growing literature suggests that DNNs outperform their classical counterparts in a variety of neuroimaging applications, yet there are few direct comparisons of relative utility. Here, we compared the performance of three DNN arch...
Article
Full-text available
The human default mode network (DMN) is implicated in several unique mental capacities. In this study, we tested whether brainwide interregional communication in the DMN can be derived from population variability in intrinsic activity fluctuations, graymatter morphology, and fiber tract anatomy. In a sample of 10,000 UK Biobank participants, patter...
Preprint
Full-text available
Individuals with Alzheimer’s disease (AD) dementia exhibit significant heterogeneity across clinical symptoms, atrophy patterns, and spatial distribution of Tau deposition. Most previous studies of AD heterogeneity have focused on atypical clinical subtypes, defined subtypes with a single modality, or restricted their analyses to a priori brain reg...
Article
Full-text available
A defining aspect of brain organization is its spatial heterogeneity, which gives rise to multiple topographies at different scales. Brain parcellation — defining distinct partitions in the brain, be they areas or networks that comprise multiple discontinuous but closely interacting regions — is thus fundamental for understanding brain organization...
Article
Full-text available
The human brain network is modular--comprised of communities of tightly interconnected nodes. This network contains local hubs, which have many connections within their own communities, and connector hubs, which have connections diversely distributed across communities. A mechanistic understanding of these hubs and how they support cognition has no...