Detecting stable individual differences in the functional organization of the human basal ganglia

ABSTRACT Moving from group level to individual level functional parcellation maps is a critical step for developing a rich understanding of the links between individual variation in functional network architecture and cognitive and clinical phenotypes. Still, the identification of functional units in the brain based on intrinsic functional connectivity and its dynamic variations between and within subjects remains challenging. Recently, the bootstrap analysis of stable clusters (BASC) framework was developed to quantify the stability of functional brain networks both across and within subjects. This multi‐level approach utilizes bootstrap resampling for both individual and group‐level clustering to delineate functional units based on their consistency across and within subjects, while providing a measure of their stability. Here, we optimized the BASC framework for functional parcellation of the basal ganglia by investigating a variety of clustering algorithms and similarity measures. Reproducibility and test‐retest reliability were computed to validate this analytic framework as a tool to describe inter‐individual differences in the stability of functional networks. The functional parcellation revealed by stable clusters replicated previous divisions found in the basal ganglia based on intrinsic functional connectivity. While we found moderate to high reproducibility, test‐retest reliability was high at the boundaries of the functional units as well as within their cores. This is interesting because the boundaries between functional networks have been shown to explain most individual phenotypic variability. The current study provides evidence for the consistency of the parcellation of the basal ganglia, and provides the first group level parcellation built from individual‐level cluster solutions. These novel results demonstrate the utility of BASC for quantifying inter‐individual differences in the functional organization of brain regions, and encourage usage in future studies. HIGHLIGHTSReproducible and reliable individual level parcellations of the basal ganglia.Parcellation consistent across sites, session, and clustering techniques.Provides a basis to study individual differences in brain parcellation.

[1]  Marisa O. Hollinshead,et al.  The organization of the human cerebral cortex estimated by intrinsic functional connectivity. , 2011, Journal of neurophysiology.

[2]  Michael Brady,et al.  Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images , 2002, NeuroImage.

[3]  A. Graybiel.  Habits, rituals, and the evaluative brain. , 2008, Annual review of neuroscience.

[4]  Donald W. Bouldin,et al.  A Cluster Separation Measure , 1979, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Pamela Guevara,et al.  Altered structural connectivity of cortico-striato-pallido-thalamic networks in Gilles de la Tourette syndrome , 2014, Brain : a journal of neurology.

[6]  Jesper Andersson,et al.  A multi-modal parcellation of human cerebral cortex , 2016, Nature.

[7]  Alexander Opitz,et al.  An integrated framework for targeting functional networks via transcranial magnetic stimulation , 2016, NeuroImage.

[8]  C. Kelly,et al.  Relationship between cingulo-insular functional connectivity and autistic traits in neurotypical adults. , 2009, The American journal of psychiatry.

[9]  A. Dagher,et al.  Basal ganglia functional connectivity based on a meta-analysis of 126 positron emission tomography and functional magnetic resonance imaging publications. , 2006, Cerebral cortex.

[10]  Matthew F. Glasser,et al.  In vivo architectonics: A cortico-centric perspective , 2014, NeuroImage.

[11]  Damien A. Fair,et al.  Defining functional areas in individual human brains using resting functional connectivity MRI , 2008, NeuroImage.

[12]  S. Swinnen,et al.  The neural basis of central proprioceptive processing in older versus younger adults: An important sensory role for right putamen , 2012, Human brain mapping.

[13]  Xian Liu,et al.  Enhanced Functional Connectivity between Putamen and Supplementary Motor Area in Parkinson’s Disease Patients , 2013, PloS one.

[14]  Ravi S. Menon,et al.  Phase based venous suppression in resting-state BOLD GE-fMRI , 2014, NeuroImage.

[15]  Satrajit S. Ghosh,et al.  Nipype: A Flexible, Lightweight and Extensible Neuroimaging Data Processing Framework in Python , 2011, Front. Neuroinform..

[16]  Jean-Baptiste Poline,et al.  Which fMRI clustering gives good brain parcellations? , 2014, Front. Neurosci..

[17]  Andrew B. Templeman,et al.  Non-Linear Optimisation in Civil Engineering , 1982 .

[18]  Xi-Nian Zuo,et al.  Assessing Variations in Areal Organization for the Intrinsic Brain: From Fingerprints to Reliability , 2016, bioRxiv.

[19]  Abraham Z. Snyder,et al.  Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion , 2012, NeuroImage.

[20]  S. Swinnen,et al.  Functional Brain Activation Associated with Inhibitory Control Deficits in Older Adults. , 2016, Cerebral cortex.

[21]  Alan C. Evans,et al.  Multi-level bootstrap analysis of stable clusters in resting-state fMRI , 2009, NeuroImage.

[22]  S. Haber.  The primate basal ganglia: parallel and integrative networks , 2003, Journal of Chemical Neuroanatomy.

[23]  Satoshi Ikemoto,et al.  Basal ganglia circuit loops, dopamine and motivation: A review and enquiry , 2015, Behavioural Brain Research.

[24]  R. Buckner,et al.  Resting-state networks link invasive and noninvasive brain stimulation across diverse psychiatric and neurological diseases , 2014, Proceedings of the National Academy of Sciences.

[25]  M. Jenkinson.  Non-linear registration aka Spatial normalisation , 2007 .

[26]  H. Künzle,et al.  Projections from the primary somatosensory cortex to basal ganglia and thalamus in the monkey , 1977, Experimental Brain Research.

[27]  Marcel van Gerven,et al.  Probabilistic model-based functional parcellation reveals a robust, fine-grained subdivision of the striatum , 2015, NeuroImage.

[28]  Catie Chang,et al.  Time–frequency dynamics of resting-state brain connectivity measured with fMRI , 2010, NeuroImage.

[29]  S. Hyman,et al.  Neural mechanisms of addiction: the role of reward-related learning and memory. , 2006, Annual review of neuroscience.

[30]  Richard S. J. Frackowiak,et al.  Evidence for Segregated and Integrative Connectivity Patterns in the Human Basal Ganglia , 2008, The Journal of Neuroscience.

[31]  R Cameron Craddock,et al.  A whole brain fMRI atlas generated via spatially constrained spectral clustering , 2012, Human brain mapping.

[32]  W. Skaggs,et al.  The Cerebellum , 2016 .

[33]  L. K. Hansen,et al.  On Clustering fMRI Time Series , 1999, NeuroImage.

[34]  M. P. van den Heuvel,et al.  Normalized Cut Group Clustering of Resting-State fMRI Data , 2008, PloS one.

[35]  Susanne M. Jaeggi,et al.  Resting state cortico-cerebellar functional connectivity networks: a comparison of anatomical and self-organizing map approaches , 2012, Front. Neuroanat..

[36]  D. Margulies,et al.  Development of anterior cingulate functional connectivity from late childhood to early adulthood. , 2009, Cerebral cortex.

[37]  Central Mechanisms , 2001, International Journal of Obesity.

[38]  Russell A. Poldrack,et al.  Large-scale automated synthesis of human functional neuroimaging data , 2011, Nature Methods.

[39]  Michael P. Milham,et al.  A convergent functional architecture of the insula emerges across imaging modalities , 2012, NeuroImage.

[40]  Christine L. Cox,et al.  The balance between feeling and knowing: affective and cognitive empathy are reflected in the brain's intrinsic functional dynamics. , 2012, Social cognitive and affective neuroscience.

[41]  R W Cox,et al.  AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. , 1996, Computers and biomedical research, an international journal.

[42]  Kae Nakamura,et al.  Central mechanisms of motor skill learning , 2002, Current Opinion in Neurobiology.

[43]  Thomas Wichmann,et al.  Circuits and circuit disorders of the basal ganglia. , 2007, Archives of neurology.

[44]  Hae-Jeong Park,et al.  Functional connectivity‐based identification of subdivisions of the basal ganglia and thalamus using multilevel independent component analysis of resting state fMRI , 2013, Human brain mapping.

[45]  Stephen M. Smith,et al.  A global optimisation method for robust affine registration of brain images , 2001, Medical Image Anal..

[46]  R. Buckner,et al.  Parcellating Cortical Functional Networks in Individuals , 2015, Nature Neuroscience.

[47]  Yaniv Assaf,et al.  Cluster analysis of resting-state fMRI time series , 2009, NeuroImage.

[48]  Xi-Nian Zuo,et al.  Resting-State Functional Connectivity Indexes Reading Competence in Children and Adults , 2011, The Journal of Neuroscience.

[49]  Xi-Nian Zuo,et al.  Reliable intrinsic connectivity networks: Test–retest evaluation using ICA and dual regression approach , 2010, NeuroImage.

[50]  M. Petrides,et al.  Broca’s region: linking human brain functional connectivity data and non‐human primate tracing anatomy studies , 2010, The European journal of neuroscience.

[51]  Keith Heberlein,et al.  Imaging human connectomes at the macroscale , 2013, Nature Methods.

[52]  Stephen M. Smith,et al.  Spatially constrained hierarchical parcellation of the brain with resting-state fMRI , 2013, NeuroImage.

[53]  L. R. Dice.  Measures of the Amount of Ecologic Association Between Species , 1945 .

[54]  M. Merello,et al.  [Functional anatomy of the basal ganglia]. , 2000, Revista de neurologia.

[55]  L. Uddin,et al.  Functional Brain Correlates of Social and Nonsocial Processes in Autism Spectrum Disorders: An Activation Likelihood Estimation Meta-Analysis , 2009, Biological Psychiatry.

[56]  Linda B. Smith,et al.  Developmental process emerges from extended brain–body–behavior networks , 2014, Trends in Cognitive Sciences.

[57]  Aki Nikolaidis,et al.  Network dynamics theory of human intelligence , 2018 .

[58]  B. Biswal,et al.  Functional connectivity of human striatum: a resting state FMRI study. , 2008, Cerebral cortex.

[59]  Essa Yacoub,et al.  The Evaluation of Preprocessing Choices in Single-Subject BOLD fMRI Using NPAIRS Performance Metrics , 2003, NeuroImage.

[60]  R. Buckner,et al.  The organization of the human striatum estimated by intrinsic functional connectivity. , 2012, Journal of neurophysiology.

[61]  C. Kelly,et al.  The extrinsic and intrinsic functional architectures of the human brain are not equivalent. , 2013, Cerebral cortex.

[62]  Nicole Wenderoth,et al.  Brain Activity during Ankle Proprioceptive Stimulation Predicts Balance Performance in Young and Older Adults , 2011, The Journal of Neuroscience.

[63]  Eleanor H. Simpson,et al.  A Possible Role for the Striatum in the Pathogenesis of the Cognitive Symptoms of Schizophrenia , 2010, Neuron.

[64]  J. Fleiss,et al.  Intraclass correlations: uses in assessing rater reliability. , 1979, Psychological bulletin.

[65]  Pierre Bellec,et al.  A BOOTSTRAP TEST TO INVESTIGATE CHANGES IN BRAIN CONNECTIVITY FOR FUNCTIONAL MRI , 2008 .

[66]  P. Strick,et al.  The cerebellum communicates with the basal ganglia , 2005, Nature Neuroscience.

[67]  Anthony G. Hudetz,et al.  6541 Enhanced Functional Connectivity of the Precuneus in Propofol Sedation , 2013 .

[68]  Jonathan D. Power,et al.  Identifying Basal Ganglia Divisions in Individuals Using Resting-State Functional Connectivity MRI , 2010, Front. Syst. Neurosci..

[69]  Angela R. Laird,et al.  Functional connectivity modeling of consistent cortico-striatal degeneration in Huntington's disease , 2015, NeuroImage: Clinical.

[70]  Mark W. Woolrich,et al.  Network modelling methods for FMRI , 2011, NeuroImage.

[71]  Russell A. Poldrack,et al.  In praise of tedious anatomy , 2007, NeuroImage.

[72]  Bharat B. Biswal,et al.  Inter-individual differences in resting-state functional connectivity predict task-induced BOLD activity , 2010, NeuroImage.

[73]  Evan M. Gordon,et al.  Individual Variability of the System‐Level Organization of the Human Brain , 2015, Cerebral cortex.

[74]  Peter Stiers,et al.  Unravelling the Intrinsic Functional Organization of the Human Lateral Frontal Cortex: A Parcellation Scheme Based on Resting State fMRI , 2012, The Journal of Neuroscience.

[75]  Steen Moeller,et al.  Multiband multislice GE‐EPI at 7 tesla, with 16‐fold acceleration using partial parallel imaging with application to high spatial and temporal whole‐brain fMRI , 2010, Magnetic resonance in medicine.

[76]  Daniel S. Margulies,et al.  Prioritizing spatial accuracy in high-resolution fMRI data using multivariate feature weight mapping , 2014, Front. Neurosci..

[77]  Alvaro Pascual-Leone,et al.  Identification of reproducible individualized targets for treatment of depression with TMS based on intrinsic connectivity , 2013, NeuroImage.

[78]  Justin L. Vincent,et al.  Precuneus shares intrinsic functional architecture in humans and monkeys , 2009, Proceedings of the National Academy of Sciences.

[79]  Michael P. Milham,et al.  Dimensional Brain-Behavior Relationships in Children with Attention-Deficit/Hyperactivity Disorder , 2012, Biological Psychiatry.

[80]  P. Sopp.  Cluster analysis. , 1996, Veterinary immunology and immunopathology.

[81]  Stephen M. Rao,et al.  Human Brain Language Areas Identified by Functional Magnetic Resonance Imaging , 1997, The Journal of Neuroscience.

[82]  G. E. Alexander,et al.  Parallel organization of functionally segregated circuits linking basal ganglia and cortex. , 1986, Annual review of neuroscience.

[83]  Wolfgang M. Pauli,et al.  Regional specialization within the human striatum for diverse psychological functions , 2016, Proceedings of the National Academy of Sciences.

[84]  Bharat B. Biswal,et al.  The oscillating brain: Complex and reliable , 2010, NeuroImage.

[85]  J. Penney,et al.  The functional anatomy of basal ganglia disorders , 1989, Trends in Neurosciences.

[86]  B. Biswal,et al.  The resting brain: unconstrained yet reliable. , 2009, Cerebral cortex.

[87]  J. Kwon,et al.  Unravelling the Intrinsic Functional Organization of the Human Striatum: A Parcellation and Connectivity Study Based on Resting-State fMRI , 2014, PloS one.

[88]  Jonathan D. Power,et al.  Multi-task connectivity reveals flexible hubs for adaptive task control , 2013, Nature Neuroscience.

[89]  Evan M. Gordon,et al.  Functional System and Areal Organization of a Highly Sampled Individual Human Brain , 2015, Neuron.