Core and matrix thalamic sub-populations relate to spatio-temporal cortical connectivity gradients

Recent neuroimaging experiments have defined low-dimensional gradients of functional connectivity in the cerebral cortex that subserve a spectrum of capacities that span from sensation to cognition. Despite well-known anatomical connections to the cortex, the subcortical areas that support cortical functional organization have been relatively overlooked. One such structure is the thalamus, which maintains extensive anatomical and functional connections with the cerebral cortex across the cortical mantle. The thalamus has a heterogeneous cytoarchitecture, with at least two distinct cell classes that send differential projections to the cortex: granular-projecting ‘Core’ cells and supragranular-projecting ‘Matrix’ cells. Here we use high-resolution 7T resting-state fMRI data and the relative amount of two calcium-binding proteins, parvalbumin and calbindin, to infer the relative distribution of these two cell-types (Core and Matrix, respectively) in the thalamus. First, we demonstrate that thalamocortical connectivity recapitulates large-scale, low-dimensional connectivity gradients within the cerebral cortex. Next, we show that diffusely-projecting Matrix regions preferentially correlate with cortical regions with longer intrinsic fMRI timescales. We then show that the Core–Matrix architecture of the thalamus is important for understanding network topology in a manner that supports dynamic integration of signals distributed across the brain. Finally, we replicate our main results in a distinct 3T resting-state fMRI dataset. Linking molecular and functional neuroimaging data, our findings highlight the importance of the thalamic organization for understanding low-dimensional gradients of cortical connectivity.

[1]  A. Bernacchia,et al.  Hierarchy of transcriptomic specialization across human cortex captured by structural neuroimaging topography , 2018, Nature Neuroscience.

[2]  Satrajit S. Ghosh,et al.  Functional gradients of the cerebellum , 2018, bioRxiv.

[3]  Manojkumar Saranathan,et al.  A systematic comparison of structural-, structural connectivity-, and functional connectivity-based thalamus parcellation techniques , 2019, Brain Structure and Function.

[4]  Daniel S. Margulies,et al.  NeuroVault.org: A repository for sharing unthresholded statistical maps, parcellations, and atlases of the human brain , 2016, NeuroImage.

[5]  Jens Wilting,et al.  Inferring collective dynamical states from widely unobserved systems , 2016, Nature Communications.

[6]  Randy L. Buckner,et al.  The evolution of distributed association networks in the human brain , 2013, Trends in Cognitive Sciences.

[7]  Thomas T. Liu,et al.  A component based noise correction method (CompCor) for BOLD and perfusion based fMRI , 2007, NeuroImage.

[8]  R Nieuwenhuys,et al.  The morphological pattern of the vertebrate brain. , 1999, European journal of morphology.

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

[10]  James M. Shine,et al.  Subcortical contributions to large-scale network communication , 2016, Neuroscience & Biobehavioral Reviews.

[11]  E. G. Jones,et al.  The thalamic matrix and thalamocortical synchrony , 2001, Trends in Neurosciences.

[12]  Matthew J. Brookes,et al.  Relationships between cortical myeloarchitecture and electrophysiological networks , 2016, Proceedings of the National Academy of Sciences.

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

[14]  Michael Breakspear,et al.  The modulation of neural gain facilitates a transition between functional segregation and integration in the brain , 2017, bioRxiv.

[15]  Laura E. Suárez,et al.  Gradients of structure–function tethering across neocortex , 2019, Proceedings of the National Academy of Sciences.

[16]  M. Mallar Chakravarty,et al.  Normative brain size variation and brain shape diversity in humans , 2018, Science.

[17]  Olaf Sporns,et al.  Complex network measures of brain connectivity: Uses and interpretations , 2010, NeuroImage.

[18]  G. Rees,et al.  Atypical intrinsic neural timescale in autism , 2019, eLife.

[19]  M. A. Muñoz,et al.  Griffiths phases and the stretching of criticality in brain networks , 2013, Nature Communications.

[20]  Krzysztof J. Gorgolewski,et al.  The Dynamics of Functional Brain Networks: Integrated Network States during Cognitive Task Performance , 2015, Neuron.

[21]  R. Faull,et al.  The distribution of calbindin, calretinin and parvalbumin immunoreactivity in the human thalamus , 2000, Journal of Chemical Neuroanatomy.

[22]  Guillén Fernández,et al.  The functional organisation of the hippocampus along its long axis is gradual and predicts recollection , 2018, Cortex.

[23]  Peter H. Schurr,et al.  Human Thalamus , 1970 .

[24]  E. G. Jones,et al.  Synchrony in the Interconnected Circuitry of the Thalamus and Cerebral Cortex , 2009, Annals of the New York Academy of Sciences.

[25]  David J. Freedman,et al.  A hierarchy of intrinsic timescales across primate cortex , 2014, Nature Neuroscience.

[26]  Ben D. Fulcher,et al.  A practical guide to linking brain-wide gene expression and neuroimaging data , 2018, NeuroImage.

[27]  Yuri B. Saalmann,et al.  Thalamus Modulates Consciousness via Layer-Specific Control of Cortex , 2020, Neuron.

[28]  S. Quake,et al.  Continuous and Discrete Neuron Types of the Adult Murine Striatum , 2019, Neuron.

[29]  D. McCormick,et al.  Actions of norepinephrine in the cerebral cortex and thalamus: implications for function of the central noradrenergic system. , 1991, Progress in brain research.

[30]  Alan C. Evans,et al.  Microstructural and functional gradients are increasingly dissociated in transmodal cortices , 2019, PLoS biology.

[31]  Guillén Fernández,et al.  The functional organisation of the hippocampus along its long axis is gradual and predicts recollection , 2018 .

[32]  E. Kuramoto,et al.  Two types of thalamocortical projections from the motor thalamic nuclei of the rat: a single neuron-tracing study using viral vectors. , 2009, Cerebral cortex.

[33]  Andrew Zalesky,et al.  Reconfiguration of Brain Network Architectures between Resting-State and Complexity-Dependent Cognitive Reasoning , 2017, The Journal of Neuroscience.

[34]  Ben D. Fulcher,et al.  Timescales of spontaneous fMRI fluctuations relate to structural connectivity in the brain , 2019, bioRxiv.

[35]  C. Gaál [About hierarchy]. , 2003, Orvosi Hetilap.

[36]  Elizabeth Jefferies,et al.  Situating the default-mode network along a principal gradient of macroscale cortical organization , 2016, Proceedings of the National Academy of Sciences.

[37]  Vince D. Calhoun,et al.  Questions and controversies in the study of time-varying functional connectivity in resting fMRI , 2020, Network Neuroscience.

[38]  Michael Breakspear,et al.  The Low-Dimensional Neural Architecture of Cognitive Complexity Is Related to Activity in Medial Thalamic Nuclei , 2019, Neuron.

[39]  Christian Lambert,et al.  Defining thalamic nuclei and topographic connectivity gradients in vivo , 2017, NeuroImage.

[40]  Michael M. Halassa,et al.  Thalamocortical Circuit Motifs: A General Framework , 2019, Neuron.

[41]  H. Barbas,et al.  The Structural Model: a theory linking connections, plasticity, pathology, development and evolution of the cerebral cortex , 2019, Brain Structure and Function.

[42]  Oluwasanmi Koyejo,et al.  Human cognition involves the dynamic integration of neural activity and neuromodulatory systems , 2019, Nature Neuroscience.

[43]  Maxwell A. Bertolero,et al.  The Human Thalamus Is an Integrative Hub for Functional Brain Networks , 2016, The Journal of Neuroscience.

[44]  Paul R. Martin,et al.  Fractal spike dynamics and neuronal coupling in the primate visual system , 2020, The Journal of physiology.

[45]  John D. Murray,et al.  Hierarchical Heterogeneity across Human Cortex Shapes Large-Scale Neural Dynamics , 2019, Neuron.

[46]  Jonathan Smallwood,et al.  Converging evidence for the role of transmodal cortex in cognition , 2017, Proceedings of the National Academy of Sciences.

[47]  P. Rakić,et al.  Neurogenetic gradients in the superior and inferior colliculi of the rhesus monkey , 1981, The Journal of comparative neurology.

[48]  D. Heeger,et al.  Slow Cortical Dynamics and the Accumulation of Information over Long Timescales , 2012, Neuron.

[49]  Carmen Varela,et al.  Thalamic neuromodulation and its implications for executive networks , 2014, Front. Neural Circuits.

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

[51]  H. Stanley,et al.  Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series. , 1995, Chaos.

[52]  Leonardo L. Gollo Exploring atypical timescales in the brain , 2019, eLife.

[53]  Stephen C. Strother,et al.  The suppression of scale-free fMRI brain dynamics across three different sources of effort: aging, task novelty and task difficulty , 2016, Scientific Reports.

[54]  P. Cisek Resynthesizing behavior through phylogenetic refinement , 2019, Attention, Perception, & Psychophysics.

[55]  Karl J. Friston,et al.  Canonical Microcircuits for Predictive Coding , 2012, Neuron.

[56]  Boris C. Bernhardt,et al.  Gradients of structure–function tethering across neocortex , 2019, Proceedings of the National Academy of Sciences.

[57]  Ulman Lindenberger,et al.  Local temporal variability reflects functional integration in the human brain , 2018, NeuroImage.

[58]  F. Clascá,et al.  Unveiling the diversity of thalamocortical neuron subtypes , 2012, The European journal of neuroscience.

[59]  M. Herkenham The afferent and efferent connections of the ventromedial thalamic nucleus in the rat , 1979, The Journal of comparative neurology.

[60]  Jonathan D. Power,et al.  Evidence for Hubs in Human Functional Brain Networks , 2013, Neuron.

[61]  Aditya Gilra,et al.  Thalamic regulation of switching between cortical representations enables cognitive flexibility , 2018, Nature Neuroscience.

[62]  D. Jacobowitz,et al.  Distribution of calretinin, calbindin-D28k, and parvalbumin in the rat thalamus , 1994, Brain Research Bulletin.

[63]  P. Fries A mechanism for cognitive dynamics: neuronal communication through neuronal coherence , 2005, Trends in Cognitive Sciences.

[64]  Allan R. Jones,et al.  An anatomically comprehensive atlas of the adult human brain transcriptome , 2012, Nature.

[65]  Ralf D. Wimmer,et al.  Thalamic amplification of cortical connectivity sustains attentional control , 2017, Nature.

[66]  Evan M. Gordon,et al.  Local-Global Parcellation of the Human Cerebral Cortex From Intrinsic Functional Connectivity MRI , 2017, bioRxiv.

[67]  A. Morel,et al.  Multiarchitectonic and stereotactic atlas of the human thalamus , 1997, The Journal of comparative neurology.

[68]  H. Kennedy,et al.  A Large-Scale Circuit Mechanism for Hierarchical Dynamical Processing in the Primate Cortex , 2015, Neuron.

[69]  Siegfried Kasper,et al.  Spatial analysis and high resolution mapping of the human whole-brain transcriptome for integrative analysis in neuroimaging , 2018, NeuroImage.

[70]  M. Larkum,et al.  General Anesthesia Decouples Cortical Pyramidal Neurons , 2020, Cell.

[71]  Shawn R. Olsen,et al.  Gain control by layer six in cortical circuits of vision , 2012, Nature.

[72]  R. Llinás,et al.  Bursting of thalamic neurons and states of vigilance. , 2006, Journal of neurophysiology.

[73]  Han Liu,et al.  Hurst Exponent Analysis of Resting-State fMRI Signal Complexity across the Adult Lifespan , 2018, Front. Neurosci..

[74]  K. Niemann,et al.  The Morel Stereotactic Atlas of the Human Thalamus: Atlas-to-MR Registration of Internally Consistent Canonical Model , 2000, NeuroImage.

[75]  J. Beran Statistical methods for data with long-range dependence , 1992 .

[76]  M. Mesulam,et al.  From sensation to cognition. , 1998, Brain : a journal of neurology.

[77]  James W. Phillips,et al.  A repeated molecular architecture across thalamic pathways , 2019, Nature Neuroscience.

[78]  M. Witter,et al.  The intralaminar and midline nuclei of the thalamus. Anatomical and functional evidence for participation in processes of arousal and awareness , 2002, Brain Research Reviews.

[79]  David A McCormick,et al.  Brain state dependent activity in the cortex and thalamus , 2015, Current Opinion in Neurobiology.

[80]  Ji-Huan He A NEW FRACTAL DERIVATION , 2011 .

[81]  Thomas E. Nichols,et al.  Nonparametric permutation tests for functional neuroimaging: A primer with examples , 2002, Human brain mapping.

[82]  S. Sherman The thalamus is more than just a relay , 2007, Current Opinion in Neurobiology.

[83]  B. E. Keen,et al.  The Suppression , 1969 .