The DOI matches its Crossref record; 36 of the 38 references it cites were found in a registry or an index; none of the 31 sources its claims cite is checked for support yet.
An anatomically comprehensive atlas of the adult human brain transcriptome
Open accessAbstract
Neuroanatomically precise, genome-wide maps of transcript distributions are critical resources to complement genomic sequence data and to correlate functional and genetic brain architecture. Here we describe the generation and analysis of a transcriptional atlas of the adult human brain, comprising extensive histological analysis and comprehensive microarray profiling of ∼900 neuroanatomically precise subdivisions in two individuals. Transcriptional regulation varies enormously by anatomical location, with different regions and their constituent cell types displaying robust molecular signatures that are highly conserved between individuals. Analysis of differential gene expression and gene co-expression relationships demonstrates that brain-wide variation strongly reflects the distributions of major cell classes such as neurons, oligodendrocytes, astrocytes and microglia. Local neighbourhood relationships between fine anatomical subdivisions are associated with discrete neuronal subtypes and genes involved with synaptic transmission. The neocortex displays a relatively homogeneous transcriptional pattern, but with distinct features associated selectively with primary sensorimotor cortices and with enriched frontal lobe expression. Notably, the spatial topography of the neocortex is strongly reflected in its molecular topography—the closer two cortical regions, the more similar their transcriptomes. This freely accessible online data resource forms a high-resolution transcriptional baseline for neurogenetic studies of normal and abnormal human brain function.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
0 of 31 cited sources checked · 0 supported · 0 flagged
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“that are highly conserved between individuals”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Rests on an assumption: The two or three clinically unremarkable adult male brains studied are sufficiently representative of the adult human brain for the atlas's general conclusions.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“a significantly greater percentage than that observed across all genes (21%, P < 10−6, Mann–Whitney U-test).”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Global mapping of transcript distributions
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Rests on an assumption: Microarray transcript levels measured in post-mortem brain tissue reflect the in vivo transcriptional state of the corresponding brain regions.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“tyrosine hydroxylase (TH) is enriched in the substantia nigra pars compacta (SNC), ventral tegmental area (VTA), and hypothalamic supraoptic and preoptic nuclei, as well as in the locus ceruleus”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Global mapping of transcript distributions
Tests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes- Rests on an assumption: Microarray transcript levels measured in post-mortem brain tissue reflect the in vivo transcriptional state of the corresponding brain regions.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“brain-wide variation strongly reflects the distributions of major cell classes such as neurons, oligodendrocytes, astrocytes and microglia”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Rests on an assumption: Microarray transcript levels measured in post-mortem brain tissue reflect the in vivo transcriptional state of the corresponding brain regions.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“no statistically significant hemispheric differences could be identified at this fine structural level that were corroborated in both brains (paired one-sided t-tests, P < 0.01, Benjamini–Hochberg (BH)-corrected).”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Global mapping of transcript distributions
Load-bearingStrength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Rests on an assumption: The two or three clinically unremarkable adult male brains studied are sufficiently representative of the adult human brain for the atlas's general conclusions.
- Rests on an assumption: Microarray transcript levels measured in post-mortem brain tissue reflect the in vivo transcriptional state of the corresponding brain regions.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“different regions and their constituent cell types displaying robust molecular signatures”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Rests on an assumption: The two or three clinically unremarkable adult male brains studied are sufficiently representative of the adult human brain for the atlas's general conclusions.
In the paper
“many synapse-associated Gene Ontology (GO) categories13 were enriched in this gene set, even relative to the PSD genes as a whole, including synapse (GO: 0045202), synaptic vesicle (GO: 0008021), synaptic transmission (GO: 0007268), neurophysiological process (GO: 0050877) and receptor activity (GO: 0004872).”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Global mapping of transcript distributions
What the sources say
- Not checked yetcites [13] Huang da, W. Sherman, B. T. & Lempicki, R. A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nature Protocols 4, 44–57 (2009) source
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes- Rests on an assumption: Microarray transcript levels measured in post-mortem brain tissue reflect the in vivo transcriptional state of the corresponding brain regions.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We found strong corroboration of overall expression levels and fold changes between structures in all three brains (Supplementary Fig. 2).”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Global mapping of transcript distributions
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Rests on an assumption: The two or three clinically unremarkable adult male brains studied are sufficiently representative of the adult human brain for the atlas's general conclusions.
- Rests on an assumption: Microarray transcript levels measured in post-mortem brain tissue reflect the in vivo transcriptional state of the corresponding brain regions.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Regional enrichments were conserved between the two brains (note similar peaks in paired rows for Brain 1 and 2; Fig. 2a)”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Global mapping of transcript distributions
Tests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes- Rests on an assumption: The two or three clinically unremarkable adult male brains studied are sufficiently representative of the adult human brain for the atlas's general conclusions.
- Rests on an assumption: Microarray transcript levels measured in post-mortem brain tissue reflect the in vivo transcriptional state of the corresponding brain regions.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“with a highly significant correlation in differential expression relationships between structures (Pearson r = 0.46, P < 10−40).”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Global mapping of transcript distributions
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Rests on an assumption: The two or three clinically unremarkable adult male brains studied are sufficiently representative of the adult human brain for the atlas's general conclusions.
- Rests on an assumption: Microarray transcript levels measured in post-mortem brain tissue reflect the in vivo transcriptional state of the corresponding brain regions.
- It may state two separate claims as one. 22
- Probably not a substantial claim. 11
- The quote only partly states this claim. 1
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“with distinct features associated selectively with primary sensorimotor cortices and with enriched frontal lobe expression”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: The two or three clinically unremarkable adult male brains studied are sufficiently representative of the adult human brain for the atlas's general conclusions.
- Rests on an assumption: Microarray transcript levels measured in post-mortem brain tissue reflect the in vivo transcriptional state of the corresponding brain regions.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“One-hundred and seventy distinct structures were assayed at least once in both brains, and 146 structures twice or more (Supplementary Table 2).”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Global mapping of transcript distributions
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“One highly regionalized neuron-related module (M6) was enriched in the striatum (the dopamine receptorDRD1 in Fig. 2a is a hub gene).”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Global transcriptional architecture of the adult brain
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Microarray transcript levels measured in post-mortem brain tissue reflect the in vivo transcriptional state of the corresponding brain regions.
In the paper
“The gene modules identified in Brain 1 were well conserved in Brain 2 as a whole (Fig. 3b), both at the level of regional gene expression patterns (third row) and as measured by a module preservation index (fourth row) using a summary Z-statistic as described previously20.”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Global transcriptional architecture of the adult brain
What the sources say
- Not checked yetcites [20] Langfelder, P., Luo, R., Oldham, M. C. & Horvath, S. Is my network module preserved and reproducible? PLoS Comput. Biol. 7, e1001057 (2011) source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: The two or three clinically unremarkable adult male brains studied are sufficiently representative of the adult human brain for the atlas's general conclusions.
- Rests on an assumption: Microarray transcript levels measured in post-mortem brain tissue reflect the in vivo transcriptional state of the corresponding brain regions.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The results in Fig. 4b bear strong similarity to the plot in Fig. 4a, again with the neocortex and cerebellum displaying the least internal heterogeneity.”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Global transcriptional architecture of the adult brain
Strength:boosted· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Rests on an assumption: Microarray transcript levels measured in post-mortem brain tissue reflect the in vivo transcriptional state of the corresponding brain regions.
None of the sources cited for this claim have been checked yet.
In the paper
“Applied to the entire 911 sample set from Brain 1, genes were grouped into well-defined co-expression modules with specific anatomical distributions (Fig. 3a, b), consistent with previous studies in brain tissues18, 19.”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Global transcriptional architecture of the adult brain
What the sources say
- Not checked yetcites [18] Oldham, M. C. et al. Functional organization of the transcriptome in human brain. Nature Neurosci. 11, 1271–1282 (2008) source
- Not checked yetcites [19] Miller, J. A., Horvath, S. & Geschwind, D. H. Divergence of human and mouse brain transcriptome highlights Alzheimer disease pathways. Proc. Natl Acad. Sci. USA 107, 12698–12703 (2010) source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Microarray transcript levels measured in post-mortem brain tissue reflect the in vivo transcriptional state of the corresponding brain regions.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the relative position of each lobe’s samples reflects the cortical topography, with the frontal pole and occipital striate cortex at opposite ends, precentral gyrus near postcentral gyrus, and so on.”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Neocortical transcription reflects spatial topography
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Not only do samples from each lobe group together, but the relative positions of the lobes are anatomically correct.”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Neocortical transcription reflects spatial topography
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The globus pallidus and striatum have highly distinct profiles, as do several specific subcortical regions including the midbrain raphe, pontine nuclei and inferior olivary complex.”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Global transcriptional architecture of the adult brain
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Microarray transcript levels measured in post-mortem brain tissue reflect the in vivo transcriptional state of the corresponding brain regions.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Other modules showed subcortical enrichment and correspond to expression in different types of glia (M8–M12), including microglia, astrocytes and oligodendrocytes.”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Global transcriptional architecture of the adult brain
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Microarray transcript levels measured in post-mortem brain tissue reflect the in vivo transcriptional state of the corresponding brain regions.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This effect is strongest when limited to genes that are differential between gyri as above, but can also be seen using the entire ~30,000 gene set, achieving a fit of 12.48% between native and MDS coordinates (P < 10−4, Supplementary Fig. 10).”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Neocortical transcription reflects spatial topography
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“MDS-based sample correlations vary nearly linearly with 3D physical distance (Fig. 6e, inset), with a goodness of fit between native and MDS coordinates of 28.36% (P < 10−4, Supplementary Fig. 9).”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Neocortical transcription reflects spatial topography
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the first three principal components had striking selectivity for specific cortical regions (samples ordered by lobe and roughly rostral to caudal within each lobe) and were generally reproducible across both brains.”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Neocortical transcription reflects spatial topography
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These first three components accounted for a large amount of the variance (PC1: 58% in Brain 1, 42% in Brain 2; PC2: 10% in Brain 1, 11% in Brain 2; PC3: 5% in Brain 1, 8% in Brain 2; Supplementary Fig. 8).”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Neocortical transcription reflects spatial topography
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Differential expression across hippocampal subfields could be validated by ISH.”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Local patterning reflects hippocampal cytoarchitecture
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. The quote only partly states this claim.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“38 transcripts demonstrated high correlation with the striatal module (M6), and 87 transcripts with the oligodendrocyte-associated module (M12; Fig. 3c)”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Global transcriptional architecture of the adult brain
Strength:boosted· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Microarray transcript levels measured in post-mortem brain tissue reflect the in vivo transcriptional state of the corresponding brain regions.
In the paper
“conservation and divergence in brain function between humans and other species provide essential information for the understanding of drug action, which is often poorly conserved across species6.”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Introduction
What the sources say
- Not checked yetcites [6] Markou, A., Chiamulera, C., Geyer, M. A., Tricklebank, M. & Steckler, T. Removing obstacles in neuroscience drug discovery: the future path for animal models. Neuropsychopharmacology 34, 74–89 (2009) source
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“consistent with the percentage of genes expressed in mouse brain by ISH (80%; ref. 1) and fetal human brain by microarrays (76%; ref. 11).”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Global mapping of transcript distributions
What the sources say
- Not checked yetcites [1] Lein, E. S. et al. Genome-wide atlas of gene expression in the adult mouse brain. Nature 445, 168–176 (2007) source
- Not checked yetcites [11] Johnson, M. B. et al. Functional and evolutionary insights into human brain development through global transcriptome analysis. Neuron 62 494–509 S0896–6273(09)00286–4 (2009) source
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“this finding is consistent with a recent study of developing human neocortex that failed to identify hemispheric differences despite extensive efforts using microarrays and quantitative PCR11.”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Global mapping of transcript distributions
What the sources say
- Not checked yetcites [11] Johnson, M. B. et al. Functional and evolutionary insights into human brain development through global transcriptome analysis. Neuron 62 494–509 S0896–6273(09)00286–4 (2009) source
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“In rodents, brain- and transcriptome-wide, cellular-resolution maps of transcript distributions are widely useful resources to complement genomic sequence data1, 2, 3.”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Introduction
What the sources say
- Not checked yetcites [1] Lein, E. S. et al. Genome-wide atlas of gene expression in the adult mouse brain. Nature 445, 168–176 (2007) source
- Not checked yetcites [2] Diez-Roux, G. et al. A high-resolution anatomical atlas of the transcriptome in the mouse embryo. PLoS Biol. 9, e1000582 (2011) source
- Not checked yetcites [3] Baldock, R. A. et al. EMAP and EMAGE: a framework for understanding spatially organized data. Neuroinformatics 1, 309–325 (2003) source
Strength:boosted· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“we examined the 740 genes identified in the human excitatory postsynaptic density (PSD12)”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Global mapping of transcript distributions
What the sources say
- Not checked yetcites [12] Bayes, A. et al. Characterization of the proteome, diseases and evolution of the human postsynaptic density. Nature Neurosci. 14, 19–21 (2011) source
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“gyral patterns do not correlate perfectly with either cytoarchitectural or functional cortical parcellation.”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Discussion
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“testing for RNA quality (RNA integrity number >6)”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Methods > Post-mortem tissue acquisition and screening
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may state two separate claims as one.
In the paper
“which are frequently enriched in long-range projection neurons14.”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Global mapping of transcript distributions
What the sources say
- Not checked yetcites [14] Hof, P. R., Nimchinsky, E. A. & Morrison, J. H. Neurochemical phenotype of corticocortical connections in the macaque monkey: quantitative analysis of a subset of neurofilament protein-immunoreactive projection neurons in frontal, parietal, temporal, and cingulate cortices. J. Comp. Neurol. 362, 109–133 (1995) source
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The synapse-associated genes clustered into groups enriched in specific regions, indicative of a diverse set of excitatory synapse subtypes.”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Global mapping of transcript distributions
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Microarray transcript levels measured in post-mortem brain tissue reflect the in vivo transcriptional state of the corresponding brain regions.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“These two individuals were males of similar age and ethnicity and therefore do not capture population or sex diversity”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Discussion
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“the relative homogeneity of the two largest neuronal structures, with ~69 billion (cerebellar cortex) and ~16 billion (cortex) neurons out of the 86 billion neurons in the human brain33, is striking and suggests an evolutionary expansion of a canonical cortical blueprint34.”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Discussion
What the sources say
Strength:hedged· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This suggests that many genes may be quite pleiotropic with respect to brain function, and that local gene regulation in specific cytoarchitectural nuclei is the most important level of resolution.”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Global transcriptional architecture of the adult brain
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Microarray transcript levels measured in post-mortem brain tissue reflect the in vivo transcriptional state of the corresponding brain regions.
None of the sources cited for this claim have been checked yet.
In the paper
“this high degree of similarity is suggestive of a strong underlying common blueprint for the human brain transcriptome and is consistent with other recent studies of human neocortical gene expression4, 5”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Discussion
What the sources say
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“specimens with no known neuropsychiatric or neuropathological history were collected”
§ An anatomically comprehensive atlas of the adult human brain transcriptome > Methods > Post-mortem tissue acquisition and screening
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
The paper relies on this without support.
The two or three clinically unremarkable adult male brains studied are sufficiently representative of the adult human brain for the atlas's general conclusions.
“Two complete normal male brains were analysed from donors aged 24 and 39 years”
“in a small number of high-quality, clinically unremarkable brains”
The paper relies on this without support.
Microarray transcript levels measured in post-mortem brain tissue reflect the in vivo transcriptional state of the corresponding brain regions.
“RNA was isolated from each sample and used to generate labelled cRNA probes for hybridization to custom 64K Agilent microarrays.”
“The output of the data generation pipeline described above is a detailed quantitative map of transcript distribution across the entire brain.”
The paper relies on this without support.
The primary feature distinguishing the human brain from other species is the enormous expansion of the neocortex relative to total brain volume.
“The primary feature that distinguishes the human brain from that of other species is the enormous expansion of the neocortex relative to total brain volume.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“We found that the thalamic–neocortex separation is conserved in mice and recapitulated both this divide and thalamic marker genes in independent single-cell, bulk and microarray data in both mice and humans8,39,40,43”
From Single-cell multiregion dissection of Alzheimer’s disease (2024) · cites this paper as [8]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Although some brain regions relevant to AD have been studied individually at scale or jointly in samples from a few individuals8–16, a comprehensive molecular characterization of region-specific differences in AD is currently lacking”
From Single-cell multiregion dissection of Alzheimer’s disease (2024) · cites this paper as [8]
The check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“The AHBA data were corrected for batch effects and normalized to the 75% quantile, as previously described (Hawrylycz et al., 2012). BSS data also were quantile normalized.”
From Aerobic glycolysis in the human brain is associated with development and neotenous gene expression (2014) · cites this paper as Hawrylycz et al., 2012
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“RAB10 is expressed in all cell types in human and mouse brains [53, 54]”
From Linkage, whole genome sequence, and biological data implicate variants in RAB10 in Alzheimer’s disease resilience (2017) · cites this paper as [53]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“and is widely expressed in all regions of both the human and mouse brains [53, 54]”
From Linkage, whole genome sequence, and biological data implicate variants in RAB10 in Alzheimer’s disease resilience (2017) · cites this paper as [53]
Experimental — accuracy not yet measured
In the citing paper
“Recent important advances include the evaluation of spatial and temporal transcriptomes by the Allen Brain Institute and BrainSpan8,11–13”
From Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015) · cites this paper as [12]
In the citing paper
“For example, when evaluating co-expression across brain regions, hubs in modules that are associated with specific regions, such as the cerebellum, are usually markers for predominant cell types, such as granule cells11,12,26,32.”
From Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015) · cites this paper as [12]
In the citing paper
“Network approaches are particularly useful for relating whole-tissue-level changes to data from these high-resolution experiments11–13,26 (FIG. 2a).”
From Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015) · cites this paper as [12]
In the citing paper
“A major advantage of network analysis over DGE analysis is that it can identify multiple levels of molecular organization within the hierarchy of brain region, cell type, organelle and molecular pathways using only transcriptional data, and can thus enable integration with other information, such as known pathway annotations, protein interactions and other molecular profiling data11,12,26,27”
From Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015) · cites this paper as [12]
In the citing paper
“Moreover, this study found that genes in these modules have dynamic developmental trajectories, demonstrating a role for ASD risk genes in neural development.”
From Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015) · cites this paper as [12]
In the citing paper
“Given that the human brain transcriptome has a reproducible structure12,26”
From Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015) · cites this paper as [12]
In the citing paper
“The first study to do this identified co-expression modules that had cell type-specific and region-specific expression patterns using nearly 1,000 adult brain regions12,109, and identified neuronal gene-enriched modules containing ASD candidate genes and ASD GWAS signals.”
From Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015) · cites this paper as [12]
In the citing paper
“Approximately 95% of RefSeq genes are expressed in developing neocortex, compared with 84% identified using these arrays in adult23.”
From Transcriptional landscape of the prenatal human brain (2014) · cites this paper as [23]
In the citing paper
“The atlas of the mid-gestational human brain described here, part of the BrainSpan Atlas of the Developing Human Brain, builds on digital molecular brain atlasing efforts in mouse20,22,24 and adult human23 by providing transcriptome resources on prenatal specimens typically inaccessible for research.”
From Transcriptional landscape of the prenatal human brain (2014) · cites this paper as [23]
In the citing paper
“Surprisingly, it turned out that transcription profiles in the adult neocortex are relatively homogeneous throughout the cortex, although a certain level of heterogeneity still does exist (Hawrylycz et al., 2012; Kang et al., 2011; Pletikos et al., 2014)”
From Genetic Changes Shaping the Human Brain (2015) · cites this paper as Hawrylycz et al., 2012
In the citing paper
“Each have reinforced findings of significant differences in the transcriptome between neuronal cell-types, brain regions, developmental stages, and species.”
From Decoding neuroproteomics: integrating the genome, translatome and functional anatomy (2014) · cites this paper as [12]
In the citing paper
“In situ hybridization and microarray data, for example the Allen Brain Atlases (Hawrylycz et al., 2012; Lein et al., 2007), have also established that mRNA transcripts encoding these five NPPs and that many other NPPs and NP-GPCR genes are expressed differentially in many brain regions.”
From Single-cell transcriptomic evidence for dense intracortical neuropeptide networks (2019) · cites this paper as Hawrylycz et al., 2012
In the citing paper
“Despite its relative homogeneity compared to other brain regions, human neocortex shows variations in transcriptional patterns that are consistent across individuals and are correlated with topographical position across the cortical sheet3.”
From Canonical genetic signatures of the adult human brain (2015) · cites this paper as [3]
In the citing paper
“Although the anatomical sampling in this study was not cell type-specific, some of these networks appear to represent co-expression in broad cell classes such as telencephalic neurons, oligodendrocytes, astrocytes and vasculature, as observed previously3, 5.”
From Canonical genetic signatures of the adult human brain (2015) · cites this paper as [3]
Citations
Cites
Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources
Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2009) · Nature Protocols · doi:10.1038/nprot.2008.211 · Cited by 35,890
Mapping and quantifying mammalian transcriptomes by RNA-Seq
Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L., & Wold, B. (2008) · Nature Methods · doi:10.1038/nmeth.1226 · Cited by 13,696
Distributed hierarchical processing in the primate cerebral cortex
Felleman, D. J., & Van Essen, D. C. (1991) · Cerebral Cortex · doi:10.1093/cercor/1.1.1 · Cited by 7,783
A General Framework for Weighted Gene Co-Expression Network Analysis
Zhang, B., & Horvath, S. (2005) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1128 · Cited by 5,684
Self-citationGenome-wide atlas of gene expression in the adult mouse brain
Lein, E. S., Hawrylycz, M. J., Ao, N., Ayres, M., Bensinger, A., Bernard, A., Boe, A. F., Boguski, M. S., Brockway, K. S., Byrnes, E. J., et al. (2007) · Nature · doi:10.1038/nature05453 · Cited by 5,572
Self-citationHandbook of Chemical Neuroanatomy
Stern, C. D. (1986) · Neurochemistry International · doi:10.1016/0197-0186(86)90021-5 · Cited by 4,160
Preface: Cerebral Cortex Has Come of Age
Goldman, P. S., & RAKIC, P. T. (1991) · Cerebral Cortex · doi:10.1093/cercor/1.1.1-a · Cited by 3,537
Spatio-temporal transcriptome of the human brain
Kang, H. J., Kawasawa, Y. I., Cheng, F., Zhu, Y., Xu, X., Li, M., Sousa, A. M. M., Pletikos, M., Meyer, K. A., Sedmak, G., et al. (2011) · Nature · doi:10.1038/nature10523 · Cited by 2,084
Identifying biological themes within lists of genes with EASE
Hosack, D. A., Dennis, G., Sherman, B. T., Lane, H. C., & Lempicki, R. A. (2003) · Genome biology · doi:10.1186/gb-2003-4-10-r70 · Cited by 1,961
NEURONAL CIRCUITS OF THE NEOCORTEX
Douglas, R. J., & Martin, K. A. C. (2004) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.27.070203.144152 · Cited by 1,886
Flagged first, then by citations
2 of the 38 references couldn’t be matched to a known paper.
Research works printed but not linked: 1
- Hurd, Y. L. & Hall, H. in Handbook of Chemical Neuroanatomy. (Dopamine) (eds Dunnett, S.B., Bentivoglio, M., Bjorklund, A., & Hokfelt, T. ) Ch. IX 525–571 (Elsevier, 2005)
Cited by
Sorted by citations
Items 501–600 of 1,012
Extracellular proteostasis prevents aggregation during pathogenic attack
Gallotta, I., Sandhu, A., Peters, M., Haslbeck, M., Jung, R., Agilkaya, S., Blersch, J. L., Rödelsperger, C., Röseler, W., Huang, C., et al. (2020) · Nature · doi:10.1038/s41586-020-2461-z · Cited by 67
Peterson, M. P., Rosvall, K. A., Choi, J.-H., Ziegenfus, C., Tang, H., Colbourne, J. K., & Ketterson, E. D. (2013) · PLoS ONE · doi:10.1371/journal.pone.0061784 · Cited by 66
An Anatomically Resolved Mouse Brain Proteome Reveals Parkinson Disease-relevant Pathways
Jung, S. Y., Choi, J. M., Rousseaux, M. W. C., Malovannaya, A., Kim, J., Kutzera, J., Wang, Y., Huang, Y., Zhu, W., Maity, S., et al. (2017) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m116.061440 · Cited by 66
A synergetic turn in cognitive neuroscience of brain diseases
Ibanez, A., Kringelbach, M. L., & Deco, G. (2024) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2023.12.006 · Cited by 65
Veronese, M., Reis Marques, T., Bloomfield, P. S., Rizzo, G., Singh, N., Jones, D., Agushi, E., Mosses, D., Bertoldo, A., Howes, O., et al. (2018) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x17712388 · Cited by 65
Synaptic vesicle binding of α-synuclein is modulated by β- and γ-synucleins
Carnazza, K. E., Komer, L. E., Xie, Y. X., Pineda, A., Briano, J. A., Gao, V., Na, Y., Ramlall, T. F., Buchman, V. L., Eliezer, D., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.110675 · Cited by 65
Park, B., Kebets, V., Larivière, S., Hettwer, M. D., Paquola, C., van Rooij, D., Buitelaar, J. K., Franke, B., Hoogman, M., Schmaal, L., et al. (2022) · Communications Biology · doi:10.1038/s42003-022-03963-z · Cited by 65
Durán, R. C., González-Orozco, J. C., Velasco, I., & Wu, J. Q. (2022) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2022.884748 · Cited by 64
Cerebral cartography and connectomics
Sporns, O. (2015) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2014.0173 · Cited by 65
The separate effects of lipids and proteins on brain MRI contrast revealed through tissue clearing
Leuze, C. W., Aswendt, M., Ferenczi, E., Liu, C. W., Hsueh, B., Goubran, M., Tian, Q., Steinberg, G. K., Zeineh, M., Deisseroth, K. A., et al. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.04.021 · Cited by 65
Microglia recapitulate a hematopoietic master regulator network in the aging human frontal cortex
Wehrspaun, C. C., Haerty, W., & Ponting, C. P. (2015) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2015.04.008 · Cited by 64
Central amygdala circuit dynamics underlying the benzodiazepine anxiolytic effect
Griessner, J., Pasieka, M., Böhm, V., Groessl, F., Kaczanowska, J., Pliota, P., Kargl, D., Werner, B., Kaouane, N., Strobelt, S., et al. (2018) · Molecular Psychiatry · doi:10.1038/s41380-018-0310-3 · Cited by 64
Hickey, S. L., Berto, S., & Konopka, G. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.04.044 · Cited by 64
Ší́p, V., Petkoski, S., Hashemi, M., Dickscheid, T., Amunts, K., & Jirsa, V. (2023) · Science Advances · doi:10.1126/sciadv.abq7547 · Cited by 64
The cell-type underpinnings of the human functional cortical connectome
Zhang, X.-H., Anderson, K. M., Dong, H.-M., Chopra, S., Dhamala, E., Emani, P. S., Gerstein, M., Margulies, D. S., & Holmes, A. J. (2024) · Nature Neuroscience · doi:10.1038/s41593-024-01812-2 · Cited by 67
Pérez‐Palma, E., Bustos, B. I., Villamán, C., Alarcón, M. A., Ávila, M. E., Ugarte, G. D., Reyes, A. E., Opazo, C., Ferrari, G. V. D., Initiative, T. A. D. N., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0095413 · Cited by 64
Rizzo, G., Veronese, M., Expert, P., Turkheimer, F., & Bertoldo, A. (2016) · PLoS ONE · doi:10.1371/journal.pone.0148744 · Cited by 64
Veronese, M., Bodini, B., García-Lorenzo, D., Battaglini, M., Bongarzone, S., Comtat, C., Bottlaender, M., Stankoff, B., & Turkheimer, F. (2015) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1038/jcbfm.2015.120 · Cited by 64
Murray, J. D., & Anticevic, A. (2016) · Schizophrenia Research · doi:10.1016/j.schres.2016.10.021 · Cited by 64
Single‐cell RNA‐sequencing of the brain
Durán, R. C., Wei, H., & Wu, J. Q. (2017) · Clinical and Translational Medicine · doi:10.1186/s40169-017-0150-9 · Cited by 64
Liu, F., Tian, H., Li, J., Li, S., & Zhuo, C. (2018) · Brain Imaging and Behavior · doi:10.1007/s11682-018-9880-6 · Cited by 64
Decoding neuroproteomics: integrating the genome, translatome and functional anatomy
Kitchen, R. R., Rozowsky, J. S., Gerstein, M. B., & Nairn, A. C. (2014) · Nature Neuroscience · doi:10.1038/nn.3829 · Cited by 63
Limon, A., Mamdani, F., Hjelm, B. E., Vawter, M. P., & Sequeira, A. (2016) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2016.04.010 · Cited by 63
Self-citationImpact of Endothelial 18-kDa Translocator Protein on the Quantification of18F-DPA-714
Wimberley, C., Lavisse, S., Brulon, V., Peyronneau, M.-A., Leroy, C., Bodini, B., Remy, P., Stankoff, B., Buvat, I., & Bottlaender, M. (2018) · Journal of Nuclear Medicine · doi:10.2967/jnumed.117.195396 · Cited by 63
Albaugh, M. D., Orr, C., Chaarani, B., Althoff, R. R., Allgaier, N., D’Alberto, N., Hudson, K., Mackey, S., Spechler, P. A., Banaschewski, T., et al. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2017.01.003 · Cited by 63
“Finally, utilizing publicly available gene expression data collected as part of the Allen Human Brain Atlas (30), we test the extent to which the relationship between brain structure and ADHD symptomatology is correlated with patterns of dopaminergic gene expression.”
MethodAntal, B. B., van Nieuwenhuizen, H., Chesebro, A. G., Strey, H. H., Jones, D. T., Clarke, K., Weistuch, C., Ratai, E., Dill, K. A., & Mujica-Parodi, L. R. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2416433122 · Cited by 65
Functional genomics suggest neurogenesis in the adult human olfactory bulb
Lötsch, J., Schaeffeler, E., Mittelbronn, M. G. A., Winter, S., Gudziol, V., Schwarzacher, S. W., Hummel, T. R., Doehring, A., Schwab, M. G., & Ultsch, A. (2013) · Brain Structure and Function · doi:10.1007/s00429-013-0618-3 · Cited by 63
Ramsden, H. L., Sürmeli, G., McDonagh, S., & Nolan, M. F. (2015) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004032 · Cited by 63
Hoftman, G. D., Dienel, S. J., Bazmi, H. H., Zhang, Y., Chen, K., & Lewis, D. A. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2017.11.029 · Cited by 63
Generation of caudal-type serotonin neurons and hindbrain-fate organoids from hPSCs
Valiulahi, P., Vidyawan, V., Puspita, L., Oh, Y., Juwono, V. B., Sittipo, P., Friedlander, G., Yahalomi, D., Sohn, J., Lee, Y. K., et al. (2021) · Stem Cell Reports · doi:10.1016/j.stemcr.2021.06.006 · Cited by 63
Trips and neurotransmitters: Discovering principled patterns across 6850 hallucinogenic experiences
Ballentine, G., Friedman, S. F., & Bzdok, D. (2022) · Science Advances · doi:10.1126/sciadv.abl6989 · Cited by 62
Sjöstedt, E., Fagerberg, L., Hallström, B. M., Månberg, A., Mitsios, N., Nilsson, P., Pontén, F., Hökfelt, T. G. M., Uhlén, M., & Mulder, J. (2015) · PLoS ONE · doi:10.1371/journal.pone.0130028 · Cited by 62
Wolfe, K. J., Ren, H. Y., Trepte, P., & Cyr, D. (2013) · Molecular Biology of the Cell · doi:10.1091/mbc.e13-06-0315 · Cited by 62
Cell-type–based model explaining coexpression patterns of genes in the brain
Grange, P., Bohland, J. W., Okaty, B. W., Sugino, K., Bokil, H., Nelson, S. B., Ng, L., Hawrylycz, M., & Mitra, P. P. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1312098111 · Cited by 62
Self-citationOldham, S., Fulcher, B., Aquino, K. M., Arnatkevičiūtė, A., Paquola, C., Shishegar, R., & Fornito, A. (2022) · Science Advances · doi:10.1126/sciadv.abm6127 · Cited by 62
Beetz, M., Tenorth, M., & Winkler, J. (2015) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2015.7139458 · Cited by 61
Nyúl‐Tóth, Á., Suciu, M., Molnár, J., Fazakas, C., Haskó, J., Herman, H., Farkas, A. E., Kaszaki, J., Hermenean, A. O., Wilhelm, I., et al. (2016) · American Journal of Physiology-Heart and Circulatory Physiology · doi:10.1152/ajpheart.00774.2015 · Cited by 61
Targeted high throughput sequencing in hereditary ataxia and spastic paraplegia
Iqbal, Z., Rydning, S. L., Wedding, I. M., Koht, J. A., Pihlstrøm, L., Rengmark, A. H., Henriksen, S. P., Tallaksen, C. M. E., & Toft, M. (2017) · PLoS ONE · doi:10.1371/journal.pone.0174667 · Cited by 61
Ehrlich, A. T., Maroteaux, G., Robé, A., Ventéo, L., Nasseef, M. T., van Kempen, L. C. L. T., Mechawar, N., Turecki, G., Darcq, E., & Kieffer, B. L. (2018) · Communications Biology · doi:10.1038/s42003-018-0106-7 · Cited by 61
Three-dimensional synaptic organization of the human hippocampal CA1 field
Montero-Crespo, M., Dominguez-Alvaro, M., Rondon-Carrillo, P., Alonso-Nanclares, L., DeFelipe, J., & Blazquez-Llorca, L. (2020) · eLife · doi:10.7554/elife.57013 · Cited by 60
Evolution of Human Brain Atlases in Terms of Content, Applications, Functionality, and Availability
Nowinski, W. L. (2020) · Neuroinformatics · doi:10.1007/s12021-020-09481-9 · Cited by 60
Temporal complexity of fMRI is reproducible and correlates with higher order cognition
Omidvarnia, A., Zalesky, A., Sina Mansour, L., Ville, D. V. D., Jackson, G. D., & Pedersen, M. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.117760 · Cited by 60
Recommendations for reproducibility of cerebrospinal fluid extracellular vesicle studies
Sandau, U. S., Magaña, S. M., Costa, J., Nolan, J. P., Ikezu, T., Vella, L. J., Jackson, H. K., Moreira, L. R., Palacio, P. L., Hill, A. F., et al. (2023) · Journal of Extracellular Vesicles · doi:10.1002/jev2.12397 · Cited by 60
Embracing variability in the search for biological mechanisms of psychiatric illness
Segal, A., Tiego, J., Parkes, L., Holmes, A. J., Marquand, A. F., & Fornito, A. (2024) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2024.09.010 · Cited by 60
Pearl, J. R., Colantuoni, C., Bergey, D. E., Funk, C. C., Shannon, P. T., Basu, B., Casella, A. M., Oshone, R. T., Hood, L., Price, N. D., et al. (2019) · Cell Systems · doi:10.1016/j.cels.2019.01.002 · Cited by 60
A systems‐level analysis highlights microglial activation as a modifying factor in common epilepsies
Altmann, A., Ryten, M., Nunzio, M. D., Ravizza, T., Tolomeo, D., Reynolds, R. H., Somani, A., Bacigaluppi, M., Iori, V., Micotti, E., et al. (2021) · Neuropathology and Applied Neurobiology · doi:10.1111/nan.12758 · Cited by 60
Drgonová, J., Walther, D. M., Wang, K. J., Hartstein, G. L., Lochte, B. C., Troncoso, J. C., Uetani, N., Iwakura, Y., & Uhl, G. R. (2015) · Molecular Medicine · doi:10.2119/molmed.2015.00017 · Cited by 60
Genetic Candidate Variants in Two Multigenerational Families with Childhood Apraxia of Speech
Peter, B., Wijsman, E. M., Nato, A. Q., Matsushita, M. M., Chapman, K. L., Stanaway, I. B., Wolff, J., Oda, K., Gabo, V. B., & Raskind, W. H. (2016) · PLoS ONE · doi:10.1371/journal.pone.0153864 · Cited by 59
Brain annotation toolbox: exploring the functional and genetic associations of neuroimaging results
Liu, Z., Rolls, E. T., Liu, Z., Zhang, K., Yang, M., Du, J., Gong, W., Cheng, W., Dai, F., Wang, H., et al. (2019) · Bioinformatics · doi:10.1093/bioinformatics/btz128 · Cited by 59
Jaffe, A. E., Tao, R., Tran, M. N., Page, S. C., Maynard, K. R., Pattie, E. A., Nguyen, C. V., Deep‐Soboslay, A., Bharadwaj, R., Young, K. A., et al. (2022) · American Journal of Psychiatry · doi:10.1176/appi.ajp.21020162 · Cited by 59
A guide to the BRAIN Initiative Cell Census Network data ecosystem
Hawrylycz, M., Martone, M. E., Ascoli, G. A., Bjaalie, J. G., Dong, H., Ghosh, S., Gillis, J., Hertzano, R. P., Haynor, D. R., Hof, P. R., et al. (2023) · PLoS Biology · doi:10.1371/journal.pbio.3002133 · Cited by 59
Self-citationQin, K., Li, H., Zhang, H., Yin, L., Wu, B., Pan, N., Chen, T., Roberts, N., Sweeney, J. A., Huang, X., et al. (2024) · Biological Psychiatry · doi:10.1016/j.biopsych.2024.01.026 · Cited by 59
Endophenotypes for Alcohol Use Disorder: An Update on the Field
Salvatore, J. E., Gottesman, I. I., & Dick, D. M. (2015) · Current Addiction Reports · doi:10.1007/s40429-015-0046-y · Cited by 59
Neurogenetic profiles delineate large-scale connectivity dynamics of the human brain
Diez, I. P., & Sepulcre, J. (2018) · Nature Communications · doi:10.1038/s41467-018-06346-3 · Cited by 59
Kutsche, L. K., Gysi, D. M., Fallmann, J., Lenk, K., Petri, R., Swiersy, A., Klapper, S. D., Pircs, K., Khattak, S., Stadler, P. F., et al. (2018) · Cell Systems · doi:10.1016/j.cels.2018.08.011 · Cited by 59
Sequeira, A., Shen, K., Gottlieb, A., & Limón, A. (2019) · Communications Biology · doi:10.1038/s42003-019-0413-7 · Cited by 59
Transcriptomic Insight Into the Polygenic Mechanisms Underlying Psychiatric Disorders
Hernandez, L. M., Kim, M., Hoftman, G. D., Haney, J. R., de la Torre-Ubieta, L., Paşaniuc, B., & Gandal, M. J. (2020) · Biological Psychiatry · doi:10.1016/j.biopsych.2020.06.005 · Cited by 59
Maurya, S. K., Bhattacharya, N., Mishra, S., Bhattacharya, A., Banerjee, P., Senapati, S., & Mishra, R. (2021) · Frontiers in Pharmacology · doi:10.3389/fphar.2021.654489 · Cited by 59
Osete, J. R., Akkouh, I. A., de Assis, D. R., Szabó, A., Frei, E., Hughes, T., Smeland, O. B., Steen, N. E., Andreassen, O. A., & Djurovic, S. (2021) · Molecular Psychiatry · doi:10.1038/s41380-021-01164-4 · Cited by 59
Merienne, N., Douce, J. L., Faivre, E., Déglon, N., & Bonvento, G. (2013) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2013.00106 · Cited by 58
Cell-type-specific labeling and profiling of glycans in living mice
Fan, X., Song, Q., Sun, D., Hao, Y., Wang, J., Wang, C., & Chen, X. (2022) · Nature Chemical Biology · doi:10.1038/s41589-022-01016-4 · Cited by 58
Neurophysiological stratification of major depressive disorder by distinct trajectories
Chen, D., Wang, X., Voon, V., Jiang, Y., Lo, C. Z., Wang, L., Shen, C., Xiang, S., Yao, S., Zhang, J., et al. (2023) · Nature Mental Health · doi:10.1038/s44220-023-00139-4 · Cited by 59
It’s not the thought that counts: Allostasis at the core of brain function
Theriault, J. E., Katsumi, Y., Reimann, H. M., Zhang, J., Deming, P., Dickerson, B. C., Quigley, K. S., & Barrett, L. F. (2025) · Neuron · doi:10.1016/j.neuron.2025.09.028 · Cited by 64
Wilken, M. S., Brzezinski, J. A., Torre, A. L., Siebenthall, K. T., Thurman, R. E., Sabo, P. J., Sandstrom, R. S., Vierstra, J. D., Canfield, T. K., Hansen, R. S., et al. (2015) · Epigenetics & Chromatin · doi:10.1186/1756-8935-8-8 · Cited by 58
Multiscale modeling of brain dynamics: from single neurons and networks to mathematical tools
Siettos, C. I., & Starke, J. (2016) · WIREs Systems Biology and Medicine · doi:10.1002/wsbm.1348 · Cited by 58
Cogill, S., & Wang, L. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw498 · Cited by 58
Ritchie, J., Pantazatos, S. P., & French, L. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.03.027 · Cited by 58
Where the genome meets the connectome: Understanding how genes shape human brain connectivity
Arnatkevičiūtė, A., Fulcher, B., Bellgrove, M. A., & Fornito, A. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118570 · Cited by 60
Neitzel, J., Franzmeier, N., Rubinski, A., Dichgans, M., Brendel, M., (ADNI), A. D. N. I., Weiner, M., Aisen, P., Petersen, R., Jack, C. R., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-23755-z · Cited by 57
Self-citationPeriodic limb movements during sleep: a narrative review
Drakatos, P., Olaithe, M., Verma, D., Ilić, K., Cash, D., Fatima, Y., Higgins, S. E., Young, A. H., Chaudhuri, К. R., Steier, J. S., et al. (2021) · Journal of Thoracic Disease · doi:10.21037/jtd-21-1353 · Cited by 57
QuNex—An integrative platform for reproducible neuroimaging analytics
Ji, J. L., Demšar, J., Fonteneau, C., Tamayo, Z., Pan, L., Kraljič, A., Matkovič, A., Purg, N., Helmer, M., Warrington, S., et al. (2023) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2023.1104508 · Cited by 57
Neuromodulatory control of complex adaptive dynamics in the brain
Shine, J. M. (2023) · Interface Focus · doi:10.1098/rsfs.2022.0079 · Cited by 58
Epigenetic modulation of brain gene networks for cocaine and alcohol abuse
Farris, S. P., Harris, R. A., & Ponomarev, I. (2015) · Frontiers in Neuroscience · doi:10.3389/fnins.2015.00176 · Cited by 57
Mahfouz, A. E., van de Giessen, M., van der Maaten, L. J. P., Huisman, S. M. H., Reinders, M. J. T., Hawrylycz, M., & Lelieveldt, B. P. F. (2014) · Methods · doi:10.1016/j.ymeth.2014.10.004 · Cited by 57
Self-citationDyslexia risk gene relates to representation of sound in the auditory brainstem
Neef, N. E., Müller, B., Liebig, J., Schaadt, G., Grigutsch, M., Gunter, T. C., Wilcke, A., Kirsten, H., Skeide, M. A., Kraft, I., et al. (2017) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2017.01.008 · Cited by 57
How Big Data and High-Performance Computing Drive Brain Science
Chen, S., He, Z., Han, X., He, X., Li, R., Zhu, H., Zhao, D., Dai, C., Zhang, Y., Lu, Z., et al. (2019) · Genomics Proteomics & Bioinformatics · doi:10.1016/j.gpb.2019.09.003 · Cited by 57
Primiani, C. T., Ryan, V. H., Rao, J. S., Cam, M. C., Ahn, K., Modi, H. R., & Rapoport, S. I. (2014) · PLoS ONE · doi:10.1371/journal.pone.0110972 · Cited by 56
Open-EASE -- A Knowledge Processing Service for Robots and Robotics/AI Researchers
Beetz, M., Tenorth, M., & Winkler, J. (2015) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · Cited by 56
Roles of the HUWE1 ubiquitin ligase in nervous system development, function and disease
Giles, A. C., & Grill, B. J. (2020) · Neural Development · doi:10.1186/s13064-020-00143-9 · Cited by 56
Understanding brain states across spacetime informed by whole-brain modelling
Vohryzek, J., Cabral, J., Vuust, P., Deco, G., & Kringelbach, M. L. (2022) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2021.0247 · Cited by 56
Park, B., Paquola, C., Bethlehem, R. A. I., Benkarim, O. M., Mišić, B., Smallwood, J., Bullmore, E. T., Bernhardt, B. C., Bullmore, E. T., Dolan, R. J., et al. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2116673119 · Cited by 56
Talishinsky, A., Downar, J. H., Vértes, P. E., Seidlitz, J., Dunlop, K., Lynch, C. J., Whalley, H. C., McIntosh, A. M., Vila‐Rodriguez, F., Daskalakis, Z. J., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-32617-1 · Cited by 56
A shifting role of thalamocortical connectivity in the emergence of cortical functional organization
Park, S., Haak, K. V., Oldham, S., Cho, H., Byeon, K., Park, B., Thomson, P., Chen, H., Gao, W., Xu, T., et al. (2024) · Nature Neuroscience · doi:10.1038/s41593-024-01679-3 · Cited by 56
Malkova, N. V., Gallagher, J. J., Yu, C. Z., Jacobs, R. E., & Patterson, P. H. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1323287111 · Cited by 56
Brain somatic mutations: the dark matter of psychiatric genetics?
Insel, T. R. (2013) · Molecular Psychiatry · doi:10.1038/mp.2013.168 · Cited by 56
Mok, K. Y., Schneider, S. A., Trabzuni, D., Stamelou, M., Edwards, M. J., Kasperavičiūtė, D., Pickering-Brown, S. M., Silverdale, M., Hardy, J., & Bhatia, K. P. (2013) · Movement Disorders · doi:10.1002/mds.25732 · Cited by 56
Eising, E., Huisman, S. M. H., Mahfouz, A. E., Vijfhuizen, L. S., Anttila, V., Winsvold, B. S., Kurth, T., Ikram, M. A., Freilinger, T. M., Kaprio, J. A., et al. (2016) · Human Genetics · doi:10.1007/s00439-016-1638-x · Cited by 56
Grassi, E., Santoro, R., Umbach, A., Grosso, A., Oliviero, S., Neri, F., Conti, L., Ala, U., Provero, P., Cunto, F. D., et al. (2019) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2018.00518 · Cited by 56
The Apelin/APJ System in Psychosis and Neuropathy
Lv, S., Chen, W., & Wang, Y. (2020) · Frontiers in Pharmacology · doi:10.3389/fphar.2020.00320 · Cited by 56
Cell type-specific manifestations of cortical thickness heterogeneity in schizophrenia
Biase, M. A. D., Geaghan, M. P., Reay, W. R., Seidlitz, J., Weickert, C. S., Pébay, A., Green, M. J., Quidé, Y., Atkins, J., Coleman, M. J., et al. (2022) · Molecular Psychiatry · doi:10.1038/s41380-022-01460-7 · Cited by 56
Oxytocin under opioid antagonism leads to supralinear enhancement of social attention
Dal Monte, O., Piva, M., Anderson, K. M., Tringides, M., Holmes, A. J., & Chang, S. W. C. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1702725114 · Cited by 55
Reduced inhibition in depression impairs stimulus processing in human cortical microcircuits
Yao, H. K., Guet-McCreight, A., Mazza, F., Moradi Chameh, H., Prevot, T. D., Griffiths, J. D., Tripathy, S. J., Valiante, T. A., Sibille, E., & Hay, E. (2022) · Cell Reports · doi:10.1016/j.celrep.2021.110232 · Cited by 55
Santos-Cortez, R. L. P., Khan, V., Khan, F. S., Mughal, Z.-U.-N., Chakchouk, I., Lee, K., Rasheed, M., Hamza, R., Acharya, A., Ullah, E., et al. (2018) · Human Genetics · doi:10.1007/s00439-018-1928-6 · Cited by 55
Wainstein, G., Rojas‐Líbano, D., Medel, V., Alnæs, D., Kolskår, K. K., Endestad, T., Laeng, B., Ossandón, T., Crossley, N. A., Matar, E., et al. (2021) · Network Neuroscience · doi:10.1162/netn_a_00205 · Cited by 55
Brain atrophy in prodromal synucleinopathy is shaped by structural connectivity and gene expression
Rahayel, S., Tremblay, C., Vo, A., Zheng, Y. Q., Lehéricy, S., Arnulf, I., Vidailhet, M., Corvol, J., ICEBERG Study Group, Vidailhet, M., et al. (2022) · Brain · doi:10.1093/brain/awac187 · Cited by 55
Cortical microstructural gradients capture memory network reorganization in temporal lobe epilepsy
Royer, J., Larivière, S., Rodríguez‐Cruces, R., Cabalo, D. G., Tavakol, S., Auer, H., Ngo, A., Park, B., Paquola, C., Smallwood, J., et al. (2023) · Brain · doi:10.1093/brain/awad125 · Cited by 55
Benchmarking methods for mapping functional connectivity in the brain
Liu, Z.-Q., Luppi, A. I., Hansen, J. Y., Tian, Y., Zalesky, A., Yeo, B. T. T., Fulcher, B., & Mišić, B. (2025) · Nature Methods · doi:10.1038/s41592-025-02704-4 · Cited by 55
Molecular‐based diagnosis of multiple sclerosis and its progressive stage
Barbour, C. R., Kosa, P. F., Komori, M., Tanigawa, M., Masvekar, R., Wu, T., Johnson, K. R., Douvaras, P., Fossati, V., Herbst, R., et al. (2017) · Annals of Neurology · doi:10.1002/ana.25083 · Cited by 55
Mapping Histological Slice Sequences to the Allen Mouse Brain Atlas Without 3D Reconstruction
Xiong, J., Ren, J., Luo, L., & Horowitz, M. (2018) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2018.00093 · Cited by 55
Virtual histology of multi-modal magnetic resonance imaging of cerebral cortex in young men
Patel, Y., Shin, J., Drakesmith, M., Evans, J., Pausova, Z., & Paus, T. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116968 · Cited by 57
Metadata
- Authors
- Hawrylycz, M. J., Lein, E. S., Guillozet-Bongaarts, A. L., Shen, E. H., Ng, L., Miller, J. A., van de Lagemaat, L. N., Smith, K. A., Ebbert, A., Riley, Z. L., Abajian, C., Beckmann, C. F., Bernard, A., Bertagnolli, D., Boe, A. F., Cartagena, P. M., Chakravarty, M. M., Chapin, M., Chong, J., Dalley, R. A., Daly, B. D., Dang, C., Datta, S., Dee, N., Dolbeare, T. A., Faber, V., Feng, D., Fowler, D. R., Goldy, J., Gregor, B. W., Haradon, Z., Haynor, D. R., Hohmann, J. G., Horvath, S., Howard, R. E., Jeromin, A., Jochim, J. M., Kinnunen, M., Lau, C., Lazarz, E. T., Lee, C., Lemon, T. A., Li, L., Li, Y., Morris, J. A., Overly, C. C., Parker, P. D., Parry, S. E., Reding, M., Royall, J. J., Schulkin, J., Sequeira, P. A., Slaughterbeck, C. R., Smith, S. C., Sodt, A. J., Sunkin, S. M., Swanson, B. E., Vawter, M. P., Williams, D., Wohnoutka, P., Zielke, H. R., Geschwind, D. H., Hof, P. R., Smith, S. M., Koch, C., Grant, S. G. N., & Jones, A. R.
- Affiliations
- Allen Institute for Brain Science (US)
- Radboud University Nijmegen (NL)
- University of California, Irvine (US)
- University of Maryland Medical Center (US)
- University of Maryland, Baltimore (US)
- University of Washington (US)
- Banyan Biomarkers (United States) (US)
- Georgetown University (US)
- University of California, Los Angeles (US)
- Icahn School of Medicine at Mount Sinai (US)
- University of Oxford (GB)
- University of Edinburgh (GB)
- Corresponding author
- Hawrylycz, Michael J.
- ORCID
- Hawrylycz, Michael J.
- Lein, Ed S.
- Guillozet-Bongaarts, Angela L.
- Ng, Lydia
- Miller, Jeremy A.
- Smith, Kimberly A.
- Beckmann, Christian F.
- Bernard, Amy
- Bertagnolli, Darren
- Chakravarty, M. Mallar
- Chapin, Mike
- Chong, Jimmy
- Dalley, Rachel A.
- Dee, Nick
- Dolbeare, Tim A.
- Feng, David
- Fowler, David R.
- Goldy, Jeff
- Gregor, Benjamin W.
- Haynor, David R.
- Hohmann, John G.
- Horvath, Steve
- Lee, Changkyu
- Li, Ling
- Li, Yang
- Parker, Patrick D.
- Reding, Melissa
- Schulkin, Jay
- Sunkin, Susan M.
- Vawter, Marquis P.
- Wohnoutka, Paul
- Geschwind, Daniel H.
- Hof, Patrick R.
- Smith, Stephen M.
- Grant, Seth G. N.
- Jones, Allan R.
- Venue
- Nature
- Published
- 2012-09
- Volume
- 489
- Issue
- 7416
- Pages
- 391-399
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC4243026
- OpenAlex
- W2055655674
- Semantic Scholar
- 44c6c5a71047351f81db358eabf87882c5232718
- Cited by
- 3,083
- References
- 38
- Citations by year
- 2026: 341 · 2025: 365 · 2024: 320 · 2023: 259 · 2022: 267 · 2021: 274 · 2020: 243 · 2019: 173 · 2018: 165 · 2017: 163 · 2016: 169 · 2015: 134 · 2014: 123 · 2013: 72 · 2012: 10
- FWCI
- 43.61
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- CaltechAUTHORS (California Institute of Technology) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- University of Twente Research Information (submittedVersion)
- Funders
- U.S. Department of Health and Human Services
- Wellcome Trust (066717, 077155)
- European Commission (241498, 242167, 241995)
- Health Resources and Services Administration
- National Institute of Standards and Technology
- U.S. Public Health Service (1C76HF15069-01-00, 1C76HF19619-01-00)
- National Institute of Mental Health (R01MH085801, R37MH060233)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- human brain transcriptome, transcriptional atlas, gene expression mapping, differential gene expression, gene co-expression, neuronal cell types, oligodendrocytes, astrocytes, microglia, primary sensorimotor cortex, frontal lobe, calbindin-D28k, hippocampus, postmortem brain, brain cell types
- MeSH terms
- Adult, Anatomy, Artistic, Animals, Atlases as Topic, Brain, Dopamine, Health, Hippocampus, Humans, Macaca mulatta, Male, RNA, Messenger, Species Specificity, In Situ Hybridization, Neocortex, Internet, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling, Databases, Genetic, Mice, Post-Synaptic Density, Transcriptome, Calbindins, S100 Calcium Binding Protein G
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-06, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-06 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review