There is no single functional atlas even for a single individual: Functional parcel definitions change with task

The goal of human brain mapping has long been to delineate the functional subunits in the brain and elucidate the functional role of each of these brain regions. Recent work has focused on whole-brain parcellation of functional Magnetic Resonance Imaging (fMRI) data to identify these subunits and create a functional atlas. Functional connectivity approaches to understand the brain at the network level require such an atlas to assess connections between parcels and extract network properties. While no single functional atlas has emerged as the dominant atlas to date, there remains an underlying assumption that such an atlas exists. Using fMRI data from a highly sampled subject as well as two independent replication data sets, we demonstrate that functional parcellations based on fMRI connectivity data reconfigure substantially and in a meaningful manner, according to brain state.

[1]  Timothy O. Laumann,et al.  Generation and Evaluation of a Cortical Area Parcellation from Resting-State Correlations. , 2016, Cerebral cortex.

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

[3]  Leonardo Cerliani,et al.  Erratum to: A new myeloarchitectonic map of the human neocortex based on data from the Vogt–Vogt school , 2014, Brain Structure and Function.

[4]  R. Cameron Craddock,et al.  Impact of the resolution of brain parcels on connectome-wide association studies in fMRI , 2015, NeuroImage.

[5]  Timothy O. Laumann,et al.  Functional Brain Networks Are Dominated by Stable Group and Individual Factors, Not Cognitive or Daily Variation , 2018, Neuron.

[6]  Sean M. Polyn,et al.  Beyond mind-reading: multi-voxel pattern analysis of fMRI data , 2006, Trends in Cognitive Sciences.

[7]  Angela R. Laird,et al.  Co-activation patterns distinguish cortical modules, their connectivity and functional differentiation , 2011, NeuroImage.

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

[9]  Stephen M Smith,et al.  The relationship between spatial configuration and functional connectivity of brain regions , 2017, bioRxiv.

[10]  Dustin Scheinost,et al.  Alterations in Anatomical Covariance in the Prematurely Born , 2015, Cerebral cortex.

[11]  T. Westfall,et al.  ALTERATIONS IN THE , 1985 .

[12]  L. Nystrom,et al.  Tracking the hemodynamic responses to reward and punishment in the striatum. , 2000, Journal of neurophysiology.

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

[14]  Mark W. Woolrich,et al.  Advances in functional and structural MR image analysis and implementation as FSL , 2004, NeuroImage.

[15]  Yu Zhang,et al.  The Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture , 2016, Cerebral cortex.

[16]  Thomas E. Nichols,et al.  Functional connectomics from resting-state fMRI , 2013, Trends in Cognitive Sciences.

[17]  Michael Esterman,et al.  Sustaining visual attention in the face of distraction: a novel gradual-onset continuous performance task , 2013, Attention, perception & psychophysics.

[18]  M. L. Fisher,et al.  An analysis of approximations for maximizing submodular set functions—I , 1978, Math. Program..

[19]  Nim Tottenham,et al.  The racially diverse affective expression (RADIATE) face stimulus set , 2018, Psychiatry Research.

[20]  Timothy O. Laumann,et al.  Functional Network Organization of the Human Brain , 2011, Neuron.

[21]  Thomas R. Knösche,et al.  Anatomical and functional parcellation of the human lateral premotor cortex , 2008, NeuroImage.

[22]  James V. Haxby,et al.  Multivariate pattern analysis of fMRI: The early beginnings , 2012, NeuroImage.

[23]  Mark W. Woolrich,et al.  Resting-state fMRI in the Human Connectome Project , 2013, NeuroImage.

[24]  B. T. Thomas Yeo,et al.  Topographic organization of the cerebral cortex and brain cartography , 2017, NeuroImage.

[25]  Marvin M. Chun,et al.  Predicting moment-to-moment attentional state , 2014, NeuroImage.

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

[27]  L. Glass Moiré Effect from Random Dots , 1969, Nature.

[28]  Mark Jenkinson,et al.  The minimal preprocessing pipelines for the Human Connectome Project , 2013, NeuroImage.

[29]  J. S. Guntupalli,et al.  Decoding neural representational spaces using multivariate pattern analysis. , 2014, Annual review of neuroscience.

[30]  M. Chun,et al.  A neuromarker of sustained attention from whole-brain functional connectivity , 2015, Nature Neuroscience.

[31]  Jonathan D. Power,et al.  Intrinsic and Task-Evoked Network Architectures of the Human Brain , 2014, Neuron.

[32]  M. Chun,et al.  Functional connectome fingerprinting: Identifying individuals based on patterns of brain connectivity , 2015, Nature Neuroscience.

[33]  S. Choi,et al.  Individual parcellation of resting fMRI with a group functional connectivity prior , 2017, NeuroImage.

[34]  Frederick Verbruggen,et al.  STOP-IT: Windows executable software for the stop-signal paradigm , 2008, Behavior research methods.

[35]  Leslie G. Ungerleider,et al.  Network analysis of cortical visual pathways mapped with PET , 1994, The Journal of neuroscience : the official journal of the Society for Neuroscience.

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

[37]  Steen Moeller,et al.  Pushing spatial and temporal resolution for functional and diffusion MRI in the Human Connectome Project , 2013, NeuroImage.

[38]  Timothy S. Coalson,et al.  Parcellations and hemispheric asymmetries of human cerebral cortex analyzed on surface-based atlases. , 2012, Cerebral cortex.

[39]  M. Delgado,et al.  Event-related functional magnetic resonance imaging of reward-related brain circuitry in children and adolescents , 2004, Biological Psychiatry.

[40]  Monica D. Rosenberg,et al.  Sustaining visual attention in the face of distraction: a novel gradual-onset continuous performance task , 2011, Attention, Perception, & Psychophysics.

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

[42]  Jacob Cohen Statistical Power Analysis for the Behavioral Sciences , 1969, The SAGE Encyclopedia of Research Design.

[43]  Andreas Krause,et al.  Budgeted Nonparametric Learning from Data Streams , 2010, ICML.

[44]  Xenophon Papademetris,et al.  Groupwise whole-brain parcellation from resting-state fMRI data for network node identification , 2013, NeuroImage.

[45]  M. Rosenberg,et al.  In the zone or zoning out? Tracking behavioral and neural fluctuations during sustained attention. , 2013, Cerebral cortex.

[46]  Evan M. Gordon,et al.  Precision Functional Mapping of Individual Human Brains , 2017, Neuron.

[47]  N. Tzourio-Mazoyer,et al.  Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain , 2002, NeuroImage.

[48]  M. Chun,et al.  Functional connectome fingerprinting: Identifying individuals based on patterns of brain connectivity , 2015, Nature Neuroscience.

[49]  Essa Yacoub,et al.  The WU-Minn Human Connectome Project: An overview , 2013, NeuroImage.

[50]  R. Nieuwenhuys The myeloarchitectonic studies on the human cerebral cortex of the Vogt–Vogt school, and their significance for the interpretation of functional neuroimaging data , 2013, Brain Structure and Function.

[51]  Amin Karbasi,et al.  A Submodular Approach to Create Individualized Parcellations of the Human Brain , 2017, MICCAI.

[52]  Jessica R. Cohen The behavioral and cognitive relevance of time-varying, dynamic changes in functional connectivity , 2017, NeuroImage.

[53]  Timothy Edward John Behrens,et al.  Task-free MRI predicts individual differences in brain activity during task performance , 2016, Science.

[54]  V. Mountcastle Modality and topographic properties of single neurons of cat's somatic sensory cortex. , 1957, Journal of neurophysiology.

[55]  Dustin Scheinost,et al.  Task-induced brain state manipulation improves prediction of individual traits , 2018, Nature Communications.

[56]  Simon B. Eickhoff,et al.  An improved framework for confound regression and filtering for control of motion artifact in the preprocessing of resting-state functional connectivity data , 2013, NeuroImage.

[57]  P. Fox,et al.  Mapping context and content: the BrainMap model , 2002, Nature Reviews Neuroscience.

[58]  S. Baron-Cohen,et al.  Another advanced test of theory of mind: evidence from very high functioning adults with autism or asperger syndrome. , 1997, Journal of child psychology and psychiatry, and allied disciplines.

[59]  D. V. Essen,et al.  Cartography and Connectomes , 2013, Neuron.

[60]  Dustin Scheinost,et al.  Unified Framework for Development, Deployment and Robust Testing of Neuroimaging Algorithms , 2011, Neuroinformatics.

[61]  Matthew F. Glasser,et al.  Parcellating Cerebral Cortex: How Invasive Animal Studies Inform Noninvasive Mapmaking in Humans , 2018, Neuron.

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

[63]  N. Kanwisher,et al.  The Human Body , 2001 .

[64]  Amin Karbasi,et al.  An exemplar-based approach to individualized parcellation reveals the need for sex specific functional networks , 2017, NeuroImage.

[65]  Mauricio R. Delgado,et al.  Savoring the Past: Positive Memories Evoke Value Representations in the Striatum , 2014, Neuron.

[66]  Abraham Z. Snyder,et al.  Function in the human connectome: Task-fMRI and individual differences in behavior , 2013, NeuroImage.

[67]  K. Brodmann Vergleichende Lokalisationslehre der Großhirnrinde : in ihren Prinzipien dargestellt auf Grund des Zellenbaues , 1985 .

[68]  B T Thomas Yeo,et al.  Reconfigurable task-dependent functional coupling modes cluster around a core functional architecture , 2014, Philosophical Transactions of the Royal Society B: Biological Sciences.

[69]  Xenophon Papademetris,et al.  More accurate Talairach coordinates for neuroimaging using non-linear registration , 2008, NeuroImage.