The Human Brainnetome Atlas and its Applications in Understanding of Brain Functions and Disorders PDF Free Download
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The Human Brainnetome Atlas and
its Applications in Understanding of
Brain Functions and Disorders
Brainnetome Center
Institute of Automation, Chinese Academy of Sciences
JUNE 12, ROME
2019 OHBM Annual Meeting
jiangtz@nlpr.ia.ac.cn
Tianzi Jiang (蒋田仔)
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Outline
The Brainnetome Atlas
Construction of Brainnetome Atlas
Validation of Brainnetome Atlas
Applications of Brainnetome Atlas
Summary and Perspectives
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What is the Brainnetome?
The Brainnetome (Brain-net-ome) takes brain network as
basic research unit, which is consists two components:
Node and Connection
It can be studied on different scales from neuron to brain
region
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Brainnetome on Three Scales
Macroscale: anatomically
distinct brain regions and
inter-regional pathways
(~250 regions in the cortex)
RegionsColumns
Mesoscale: connections
within and between
minicolumns (~2×108
minicolumn)
Neurons
Microscale: neurons and
their synaptic connections
(~ 1011 neurons and 1015
connections)
The nodes and connections of Brainnetome can be
defined at different scales and levels
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Research Themes of Brainnetome
Topological Structure of Brain Networks
(Brainnetome Atlas & Connectome)
Dynamics and Characteristics of Brain Networks
Network Manifestation of Functions and
Malfunctions of the Brain
Genetic Basis of Brain Networks
Simulating and Modeling Brain Networks on
Supercomputing Facilities
www.brainnetome.org
Jiang T, Brainnetome: A new -ome to understand the brain and
its disorders, NeuroImage, 2013
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Campbell
1905
1909
Brodmann
Flechsig
1920
1925
von Economo and Koskinas
Talairach atlas
1988 JU-Brain atlas
1996- now 3D Talairach atlas
2000
FreeSurfer DK atlas
2006, 2009 Brainnetome Atlas
2011- now
2013
Big-Brain
2002
AAL atlas
1997-now
Surface-based atlas
1995
ICBM/MNI template
Brain Atlases: in vitro & in vivo Studies
Zilles and Amunts, Nat Rev Neurosci. 2010;
Fan et al, Cerebral Cortex, 2016
Problems:Roughness, Lack of correspondence, Little sub-regional
information and Variable relations between functional borders and
macroscale landmarks
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Brodmann’s Atlas 1909
Basic Ideas for Brainnetome Atlas
Brainnetome Atlas
Parcellation Results
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Outline
The Brainnetome Atlas
Construction of Brainnetome Atlas
Validation of Brainnetome Atlas
Applications of Brainnetome Atlas
Summary and Perspectives
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Anatomical connectivity
Functional connectivity
Meta-analysis co-activation
…
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2
Rest of the brain
Seed voxels Seed voxels
Seed voxels
Connectivity matrix
Similarity matrix
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Clustering
Methodologies of the Brainnetome Atlas
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3
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Brodmann areas 7/23/31
7
31
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Area with Heterogeneous Cytoarchitectures
The parcellation results of posteromedial cortex could be well
comparable to its complex cytoarchitectonic organization
Zhang et al., Cerebral Cortex, 2014
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CoCoMac database Fiber tract patterns for 5 right PMC subregions
Connectivity Profiles Cross Species
Zhang et al., Cerebral Cortex, 2014
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Areas with Homogeneous Cytoarchitecture
Brodmann area 38
TAr
TGlTGm
Fan et al., Cerebral Cortex, 2014
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Connectivity Profiles of Sub-regions
Sub-regional connectivity patterns
Fan et al., Cerebral Cortex, 2014
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Connectivity Based Parcellation of Human Brain
Wang et al., Neuroimage 2012; Fan et al., Cerebral Cortex 2014; Liu et al., J Neuroscience 2013; Li et al, Neuroimage 2013;
Zhang et al., Cerebral Cortex 2014; Wang et al., Human Brain Mapping 2014; Zhang et al., Brain Structure & Function, 2014
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The Human Brainnetome Atlas
•The Human Brainnetome Atlas: A New Brain Atlas
Based on Connectional Architecture
•With 210 cortical and 36 subcortical sub-regions,
provides a fine-grained, cross-validated atlas and
contains information on both anatomical and
functional connections
Fan et al., Cerebral Cortex, 2016
George Paxinos
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Open Resources of Brainnetome Atlas
http://atlas.brainnetome.org
ATPP pipeline: https://www.nitrc.org/projects/atpp
Brainnetome Atlas Viewer
https://www.nitrc.org/projects/bn_atlas/ Education
Fan et al., Cerebral Cortex, 2016
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Available in Platforms and Popular Software
Neuroinformatics Platform of Human Brain Project, International Neuroinformatics
Coordinating Facility
Popular Software: SPM, FSL
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Outline
The Brainnetome Atlas
Construction of Brainnetome Atlas
Validation of Brainnetome Atlas
Applications of Brainnetome Atlas
Summary and Perspectives
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Verification of the Brainnetome Atlas
Cross-modality Comparison
Genetic Basis of Brain Parcellation
Connectivity-Function Relationship
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Criteria for Human Brain Parcellation
Connection
Inputs: determine the
information available to a
region
Outputs: determine the
influence it can have on other
brain regions
Passingham, et al., Nature Rev Neurosci, 2002；
Johansen-Berg, et al, Cerebral Cortex, 2005
Topography
Architecture
.
Function
The connectivity plays a fundamental role in
making a brain area distinct !
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Comparison of Brainnetome Atlas with JuBrain
Amunts et al., PLoS Biol, 2010
Zhang et al., NeuroImage, 2017
The topography of parcellation based on connectivity profiles is consistent with
parcellation based on cytoarchitecture
Voorn, Brady et al. 1996
Xia, Fan et al, Hum Brain Mapp, 2017
Scheperjans et al., Cereb Cortex, 2008a, 2008b
Wang et al, Hum Brain Mapp, 2014
7p
5L
hIP3
7PC 7A
Caspers et al, Neuroimage, 2006,2008
Wang et al., Neuroimage, 2012
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Multi-modal CBP of Superior Parietal Lobule
and Dorsal Premotor Cortex
Superior parietal lobule (SPL) parcellation
results using multimodal neuroimaging methods Five left dorsal premotor(PMd) cortical
modules were identified
Wang et al., Human Brain Mapping, 2015 Genon et al., Neuroimage, 2017
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Posterior Boundary of Wernicke’s Area:
Intraoperative Electrical Stimulation
Intraoperative electrical stimulation (anomia)
Wang et al., Human Brain Mapping, 2015
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Shell-Core Dichotomy of Nucleus Accumbens
2-cluster, termed shell-like and core-like divisions, provided the best description of the data
and was consistent with earlier anatomical studies on shell-core organization.
Xia et al., Human Brain Mapping, 2017
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Verification of the Brainnetome Atlas
Cross-modality Comparison
Genetic Basis of Brain Parcellation
Connectivity-Function Relationship
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Consistent Parcellation of Brain Regions
Brainnetome Atlas
JuBrain Atlas
Motor and sensory homunculi
Cytoarchitectonics
Receptor-
architectonics
Connectivity
Topographic
mapping
Gyral / sulcal
anatomy
Broca’s area divisions
-- by receptor architectonics
Amunts K et al., PLoS Biol., 2010, Zhang Y et al., NeuroImage, 2017
-- by connectivity-driven info
BrodmannAtlas
Freesurfer DK Atlas
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Genes Influence Cortical Patterning
Animal Studies Human Studies
Fine-grained intrinsic
genetic architecture of
the cortex?
Cholfin et al., PNAS, 2007, J Comp Neurol, 2008
Lobar Level
Fgf8, Fgf17, Emx2 regulate frontal cortex subdivision patterning
Chen et al., Neuron 2011
Whole Brain
O'Leary, et al., Neuron, 2007
Cortical areal development is controlled by the interplay
of intrinsic and extrinsic mechanisms
4 divisions
12 divisions
Chen et al., Science 2012
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Genetic Correlation-based Parcellation Pipeline
Twins
The genetic correlations of morphology are estimated
based on twin strategy, and built fine-grained genetic architecture.
Cui et al., Cerebral Cortex, 2016
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Genetic Ssubdivisions Corresponded to Fine-grained
Functional Specializations
Superior Medial Frontal Cortex Frontal Pole
Inferior Frontal Gyrus M1
Cui et al., Cerebral Cortex, 2016
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Genetic Correlation Correlates with Functional
Connectivity
Genetic correlation
determine cortical
patterning, which
validates the genetic
basis of the
Brainnetome atlas
Cui et al., Cerebral Cortex, 2016
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Verification of the Brainnetome Atlas
Cross-modality Comparison
Genetic Basis of Brain Parcellation
Connectivity-Function Relationship
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Why Anatomical Connectivity Profiles Can Be Used to
Construct Brainnetome Atlas
Anatomical connectivity patterns predict face selectivity in the fusiform gyrus
Whether anatomical connectivity can predict functional
activations across different cognitive domains?
Whether there exists regional difference in the
connectivity-function relationship throughout the whole
cortex are still unknown?
Saygin, Z. M. et al. Nat. Neurosci. 2012
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AC Predicts Functional Activations across
Different Cognitive Domains
Contrasts Mean
Similarity
EMOTION FACES 0.55
GAMBLING PUNISH 0.56
LANGUAGE STORY-
MATH 0.59
MOTOR T 0.42
RELATIONAL REL 0.69
SOCIAL TOM 0.68
WM 2BK 0.63
We used seven tasks
from HCP to address
the first question
Wu et al., 2019, under review
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Connectivity-function Relationship
The connectivity-function relationship(CFR)
was characterized by predicting activity from
anatomical connectivity across the cortex.
Whether there exists regional difference in the
connectivity-function relationship throughout
the whole cortex?
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Spatial Distribution of CFR in Different Contrasts
The seven functional networks that represented the functional hierarchy of the cortex
Spatial distribution of the average CFR
Wu et al., 2019, under review
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CFR Hierarchy was Correlated to Functional and
Anatomical Hierarchy
Functional
Flexibility
Functional
Variability
Myelin
Wu et al., 2019, under review
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Outline
The Brainnetome Atlas
Construction of Brainnetome Atlas
Verification of Brainnetome Atlas
Applications of Brainnetome Atlas
Summary and Perspectives
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Applications of Brainnetome Atlas
Connectivity Profiles Reveal the Translation
Subarea in the PHR
Sex-specific Neural Circuits of Emotion
Regulation
New Paradigm for Diagnosis and Therapy
of Brain Diseases
Cross-species Comparison of Nucleus
Accumbens
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In 2007，European Union has incorporated
the gray matter atrophy of MTL based on
MRI as the diagnostic markers
Lancet Neurology, 2007
Construction of the fine-grained PHR
atlas will provide important imaging
guidance for the early diagnosis of AD
Anterior PHR is an Imaging Marker for AD
Neuropathological staging of AD related changes
Braak H and Braak E.(1991)
Neurofibrillary tangles A beta
early stage end stage Patterns of grey matter atrophy identified at the
time of progression from MCI to AD
J. L. Whitwell, et al. Brain, 2007
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PRC
PHC
Anatomy of lateral parahippocampal region
Two cortical systems for memory-guided
behaviour
Ranganath, C. and Ritchey, M. (2012)
Nat Rev Neurosci
Anatomy and Functions of PHR
Inconsistent !
B. P. Staresina et al. (2011) J Neuroscience
Libby et al. (2014) J Neuroscience
Recent fMRI findings
Object coding
Location coding
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BC
Functional connectivity of left PHR
subregions Functional connectivity of PRCr, PRCc and PHC
in the hippocampus and entorhinal cortex
Parcellation of PHR with Connectivity Profiles
Zhuo et al., Journal of Neuroscience, 2016
A
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Revised Model Based New Findings
Zhuo et al., Journal of Neuroscience, 2016
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Grey matter volume decrease
degree in PHR associated with AD
Anterior Posterior
Dynamic Damages in MCI and AD
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Applications of Brainnetome Atlas
Connectivity Profiles Reveal the Translation
Subarea in the PHR
Sex-specific Neural Circuits of Emotion
Regulation
New Paradigm for Diagnosis and Therapy
of Brain Diseases
Cross-species Comparison of Nucleus
Accumbens
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Significant Gender Difference in Depression
There are gender differences in the incidence of depression:
The number of female patients with depression is much greater than
that of male patients.Female depressive disorders are also reported to
show more severe depressive symptoms than Male patients.
Dysfunction in emotion regulation is one of the main
symptom of major depression
Amygdala is the key brain region
for emotion regulation. Hence,
investigating brain functional connectivity
based on the sub-regions of amygdala
generated from precise Brainnetome Atlas
may reveal the underlying critical factors
of why mood regulation ability exist
remarkable gender differences.
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Amygdala and Emotion Regulation
Amygdala
Laterobasal nuclei group (LB),
centromedial nuclei group (CM), and
the superficial nuclei group (SF)
CM
SF
LB
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Gender-specific Networks of Emotion
Regulation in CM of Amygdala
Cognition Related Networks:
Connectivity between right CM and medial superior frontal gyrus (SFG)
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Gender-specific Networks of Emotion
Regulation in CM of Amygdala
Emotion Related Networks:
Connectivity between CM and insula and superior temporal gyrus (STG)
Wu, et al., Scientific Reports, 2016
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Applications of Brainnetome Atlas
Connectivity Profiles Reveal the Translation
Subarea in the PHR
Sex-specific Neural Circuits of Emotion
Regulation
New Paradigm for Diagnosis and Therapy
of Brain Diseases
Cross-species Comparison of Nucleus
Accumbens
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Brainnetome Atlas Based New Paradigm for
Diagnosis and Therapy of Brain Diseases
Brainnetome Atlas Based Precision Targeting
for Therapy of Parkinson Disease, Depression,
Epilepsy, Disorders of Consciousness.
Brainnetome Atlas Based New Paradigm for
the Early Diagnosis of Autism, Depression,
Schizophrenia and Alzheimer's Disease.
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Brainnetome Atlas Based Precision Targeting
for Therapy of Parkinson Disease
The therapy effectiveness of PD depends on precisely targeting
the subregions of the subthalamus nucleus
Cognition
Emotion
Motor
Beep Brain Stimulation
Pathways
STN subregions & Pathways
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Precision Therapy Based on Brainnetome Atlas
DBS Navigation and Localization
Brainnetome Atlas guided TMS on Depression
rTMS Non-rTMS NC
Patients 90 52 110
Baseline 85 43 105
Follow up 72 29 -
Transcranial MRI-Guided
Focused Ultrasound
Individual thalamic atlas
Vim
Ventral Intermediate nucleus
CM/Pf
Centromedian/Parafascicular nuclear complex
Tremor
Disorders of Consciousness
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Depression
Stoke
Martin D, et al., Neuron, 2017
Tanja C. WN et al., PLoS ONE, 2017
Zhang J et al., Scientific Reports, 2017
Hong J, et al., Neural Regen Res, 2017
Zhu J et al., JAD, 2017
Anxiety
Brain Lesion
Schizophrenia
Kargel P.A et al., Nature Neuroscience, 2017
Carolyn B.M et al., Schizophrenia Research, 2017
Tang Y, et al., Frontiers In Neuroanatomy
Alexandra A, et al., Scientific Reports, 2017
Dorinal P et al., Neuropsychologia, 2017
Roy A et al., PAIN, 2019
End-stage Renal Disease
Spina S, et al., Brain, 2019
Boran E, et al., Science Advances, 2019
Ma Jet al., Brain Imaging and Behavior, 2017
Mahlega SH et al., Neuropsychopharmacology, 2017
Son SJ, et al., PLoS ONE, 2017
Zhang Y et al., Cerebral Cortex, 2018
ADHD
Parkinson Disease
Alzheimer’s Disease
Tauopathies
Mnemonic Training
Pain, Cognitive control,
and Emotion
Emotion and Auditory
SEEG Working Memory
Chronic Jaw Pain
Applications in Brain Diseases
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Applications of Brainnetome Atlas
Connectivity Profiles Reveal the Translation
Subarea in the PHR
Sex-specific Neural Circuits of Emotion
Regulation
New Paradigm for Diagnosis and Therapy
of Brain Diseases
Cross-species Comparison of Nucleus
Accumbens
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Nucleus Accumbens: an Interface Between
Cognition, Emotion, and Action
Stan B. Floresco, Annu. Rev. Psychol. 2015
The ventral striatum, including two nucleus accumbens (Acb) subregions, the
shell and core, differ in the patterns whereby they integrate signals from
prefrontal and limbic areas of the brain.
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The Shell-core Organization of Acb
is Conserved across Species
Rat Marmoset Rhesus Monkey Human
G.E. Meredith et al.,
Journal of
Comparative
Neurolog,1996
Whether these shell and core subregions are homologous and, if so,
what is the extent of that homology?
G.E. Meredith et al., Journal of Comparative Neurology, 1996
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Tractography-Based Parcellation of Human Acb
The shell-and core-like divisions of Acb, provided the best description of
the data and was also consistent with earlier anatomical studies on shell-
core organization.
Xia et al., Human Brain Mapping, 2017
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Xia et al., 2019, under review
Tractography-Based Parcellation of Monkey Acb
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Defining Human and Macaque Comparable OMPFC
Areas
Human OMPFC CBP-based parcellation
Neubert et al., 2015
Monkey OMPFC cytoarchitecture-based parcellation
Paxinos et al., 2009; Calabrese et al., 2015
Roughly corresponding relationships for the human and macaque
OMPFC target areas
11, 11m, 13, 14m, 25, 32, and 47o
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Redefining Target OMPFC Areas
for Cross-Species Comparison
Delineated connectionally comparable targets areas in OMPFC
Neubert et al., 2015
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Cross-species Comparisons by Connectivity
Fingerprints
Xia et al., 2019, under review
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Outline
The Brainnetome Atlas
Construction of Brainnetome Atlas
Validation of Brainnetome Atlas
Applications of Brainnetome Atlas
Summary and Perspectives
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Summary
A new brain atlas –brainnetome atlas based on
connectivity profiles, and its reliability were
presented.
With the brainnetome atlas, we could get
insights into the brain function and the brand
new knowledge on the pathophysiological
mechanism of psychiatric and neurological
disorders.
It opens a new avenue to study the brain and its
disorders.
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Future in Brainnetome Atlas
Multimodal brainnetome atlas, new paradigm for the early
diagnosis and therapy, and new models for brain-inspired
computing
Brainnetome Atlas
Based Paradigm for
Diagnosis and Therapy
of Brain Disease
Brainnetome Atlas
Based Brain-inspired
Computing
Brainnetome Atlas
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Multi-modalMulti-scale
Individualized
Brainnetome Atlas
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Subcomponents of the Main Fiber Bundles
Brainnetome Atlas
IFJ
A37vl
A37lv
A39rv
Main Fiber Bundles Subcomponents of
Fiber Bundles and Connectome
CB
SLF
UNC ILF
The fasciculus is a bundle of axons that follow the same pathway,
and with origins and terminations of the same brain regions.
With Brainnetome atlas, the subcomponents in the main fiber
bundles can be identified.
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Clustering
Whole Brain Tractography
FA Map
Major Fiber Bundle
ROI Selected
SLFII-1 SLFII-2 SLF/AF-2
SLF/AF-1 SLF/AF-3
SLF/AF-5
Streamlines
Streamlines
Similarity Matrix
SLF/AF-4SLFIII-2
SLFIII-1 SLFIII-3
Brainnetome Atlas
Framework of Fiber Bundle Segmentation
Cheng et al., Poster No. Th776
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Subcomponents of SLF/AF
SLF II-1 SLF II-2
SLF/AF-1
SLF/AF-2
SLF/AF-3
SLF/AF-5
SLF/AF-4
SLF III-1 SLF III-2 SLF III-3
Cheng et al., Poster No. Th776
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Subcomponents of Cingulum Bundle
Lateral view
Medial view Cheng et al., unpublished, 2019
CB-6
CB-5
CB-4
CB-1
CB-2
CB-3
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Multi-scale Brainnetome Atlas
5-10 YearsOngoing 3-5 Years
Human Brainnetome Atlas
Healthy Cohort
Cohort with Brain Diseases
Monkey Brainnetome Atlas
Animal Models
Macro
Meso
9.4T MRI
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Mesoscale
(Structure)
PS-OCT
Tracer Imaging
Monkey
Brainnetome
Atlas
Optogenetics
Modulation
Microendoscope
Detection
9.4T MRI Connectivity Profiles Cross-species
Brainnetome Atlas
Tissue Clearing
Lightsheet
Multiscale Monkey Brainnetome Atlas
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Yue Cui Yu Zhang Congying Chu Hai Li
Chunshui Yu Huaigui Liu Wei Li
Jiaojian Wang Yaqin Zhang Junjie Zhuo
Liangfu Chen
Simon B. Eickhoff
Acknowledgement
Lingzhong Fan
Katrin Amunts Svenja Caspers
Yan Wu Luqi Cheng
Xiaoluan Xia Chen Cheng
Long Cao
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Acknowledgement
