Thirty cases were included that were collected in two centers and the sampling of the blocks was carried out by two experienced neuropathologists (IA, TA). The cases were selected based on the Braak stage to which they were assigned by IA and TA after application of silver stain. The goal was to include all severities of the disease, that is, all the various stages of AD‐related neurofibrillary pathology. The samples were taken for the routine diagnostics and obtained within a 10‐year time span. The demographics of the subjects are given in Table 1 . The selection of anatomical regions to be sampled was based on the requirements listed in current consensus criteria (NIA‐RI), and was also influenced by known general practice among neuropathologists. The specimens included were the samples from middle frontal gyrus, inferior parietal lobule, superior and middle temporal gyrus, occipital cortex including calcarine fissure, posterior hippocampus at the level of lateral geniculate nucleus and anterior hippocampus at the level of uncus. A total of eight sets of 7‐µm thick sections were produced from all six brain areas of the 30 cases.
Middle Temporal Gyrus
The Middle Temporal Gyrus is a key region of the temporal lobe, known for its involvement in various cognitive functions.
This area plays a crucial role in language processing, memory, and social cognition.
Researchers can leverage PubCompare.ai to optimize their investigations of the Middle Temporal Gyrus, identifying the most reproducible and accurate scientific protocols from the literature, preprints, and patents.
By leveraging AI-powered protocol comparisons, researchers can enhance their research effciency and productivity, gaining valuable insights to advance our understanding of this important brain region.
This area plays a crucial role in language processing, memory, and social cognition.
Researchers can leverage PubCompare.ai to optimize their investigations of the Middle Temporal Gyrus, identifying the most reproducible and accurate scientific protocols from the literature, preprints, and patents.
By leveraging AI-powered protocol comparisons, researchers can enhance their research effciency and productivity, gaining valuable insights to advance our understanding of this important brain region.
Most cited protocols related to «Middle Temporal Gyrus»
Body Regions
Brain
Calcarine Sulcus
Diagnosis
Lateral Geniculate Body
Medial Frontal Gyrus
Middle Temporal Gyrus
Neuropathologist
Occipital Lobe
Parietal Lobule
Seahorses
Silver
Stains
Gyrus, Anterior Cingulate
Inferior Temporal Gyrus
Medial Frontal Gyrus
Middle Temporal Gyrus
Occipitotemporal Gyrus, Lateral
Orbitofrontal Cortex
Tissues
Amygdaloid Body
Brain
Corpus Callosum
Dementia
Diagnosis
Endopeptidase K
Epitopes
Formaldehyde
Gyrus, Anterior Cingulate
Histological Techniques
Immunoglobulins
Knee
Lateral Geniculate Body
Lewy Bodies
Medial Frontal Gyrus
Medulla Oblongata
Microtomy
Middle Temporal Gyrus
Neurites
Olfactory Bulb
Paraffin
Paraffin Embedding
Parietal Lobule
Peptide Fragments
Pons
Serine
SNCA protein, human
Substantia Nigra
thioflavine
Tissues
The goal of this work was to create a large dataset of consistently and accurately labeled cortices. To do so we adopted a modification of the DK protocol (Desikan et al., 2006 (link)). We modified the protocol for two reasons: (i) to make the region definitions as consistent and as unambiguous as possible, and (ii) to rely on region boundaries that are well suited to FreeSurfer’s classifier algorithm, such as sulcal fundi that are approximated by surface depth and curvature. This would make it easier for experienced raters to assess and edit automatically generated labels, and to minimize errors introduced by the automatic labeling algorithm. We also sought to retain major region divisions that are of interest to the neuroimaging community. In some cases, this necessitated the inclusion of anatomically variable sulci as boundary markers (such as subdivisions of the inferior frontal gyrus) or use of gyral crowns (such as the pericalarine cortex). Alternatively, common subdivisions of gyri that were not based on cortical surface curvature features (such as subdivisions of the cingulate gyrus and the middle frontal gyrus) were retained if the subdivision was wholly within the surface curvature features that defined the gyrus.
The DKT protocol has 31 cortical regions per hemisphere, one less than the DK protocol. We have also created a variant of the DKT protocol with 25 cortical regions per hemisphere to combine regions that are subdivisions of a larger gyral formation and whose divisions are not based on sulcal landmarks or are formed by sulci that are highly variable. The regions we combined include subdivisions of the cingulate gyrus, the middle frontal gyrus, and the inferior frontal gyrus. Since fewer regions means larger regions that lead to higher overlap measures when registering images to each other, note that comparisons should be made using the same labeling protocol. We refer to these two variants as the DKT31 and DKT25 cortical labeling protocols.
Figure1 shows cortical regions in the DKT labeling protocol. We retained the coloring scheme and naming conventions of Desikan et al. (2006 (link)) for ease of comparison. The Appendix contains detailed definitions of the regions but we summarize modifications to the original DK protocol in Table 2 . Table 3 lists the names and abbreviations for the bounding sulci used by the DKT protocol; the locations of these sulci are demonstrated in Figure 2 . Three regions were eliminated from the original DK protocol: the frontal and temporal poles and the banks of the superior temporal sulcus. The poles were eliminated because their boundaries were comprised primarily of segments that “jumped” across gyri rather than along sulci. By redistributing these regions to surrounding gyri we have increased the portion of region boundaries that along similar curvature values, that is, along sulci and gyri rather than across them, which improves automatic labeling and the reliability of manual edits. The banks of the superior temporal sulcus region was eliminated because its anterior and posterior definitions were unclear and it spanned a major sulcus.
Additional, more minor, modifications took the form of establishing distinct sulcal boundaries when they approximated a boundary in the original protocol that was not clearly defined. For instance, the lateral boundary of the middle temporal gyrus anterior to the inferior frontal sulcus was defined explicitly as the lateral H-shaped orbital sulcus and the frontomarginal sulcus more anteriorly. Similarly, the boundary between the superior parietal and the lateral occipital regions was assigned to the medial segment of the transverse occipital sulcus. Other examples include establishing the rhinal sulcus and the temporal incisure as the lateral and anterior borders of the entorhinal cortex, and adding the first segment of the caudal superior temporal sulcus (Petrides, 2011 ) as part of the posterior border of the supramarginal gyrus. Several popular atlases informed these modifications, including Ono et al. (1990 ), Damasio (2005 ), Duvernoy (1999 ), and Mai et al. (2008 ). The recent sulcus and gyrus atlas from Petrides (2011 ) proved particularly useful because of its exhaustive catalog of small but common sulci.
The DKT protocol has 31 cortical regions per hemisphere, one less than the DK protocol. We have also created a variant of the DKT protocol with 25 cortical regions per hemisphere to combine regions that are subdivisions of a larger gyral formation and whose divisions are not based on sulcal landmarks or are formed by sulci that are highly variable. The regions we combined include subdivisions of the cingulate gyrus, the middle frontal gyrus, and the inferior frontal gyrus. Since fewer regions means larger regions that lead to higher overlap measures when registering images to each other, note that comparisons should be made using the same labeling protocol. We refer to these two variants as the DKT31 and DKT25 cortical labeling protocols.
Figure
Additional, more minor, modifications took the form of establishing distinct sulcal boundaries when they approximated a boundary in the original protocol that was not clearly defined. For instance, the lateral boundary of the middle temporal gyrus anterior to the inferior frontal sulcus was defined explicitly as the lateral H-shaped orbital sulcus and the frontomarginal sulcus more anteriorly. Similarly, the boundary between the superior parietal and the lateral occipital regions was assigned to the medial segment of the transverse occipital sulcus. Other examples include establishing the rhinal sulcus and the temporal incisure as the lateral and anterior borders of the entorhinal cortex, and adding the first segment of the caudal superior temporal sulcus (Petrides, 2011 ) as part of the posterior border of the supramarginal gyrus. Several popular atlases informed these modifications, including Ono et al. (1990 ), Damasio (2005 ), Duvernoy (1999 ), and Mai et al. (2008 ). The recent sulcus and gyrus atlas from Petrides (2011 ) proved particularly useful because of its exhaustive catalog of small but common sulci.
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Conferences
Cortex, Cerebral
Crowns
Entorhinal Area
Frontal Sulcus
Gyrus Cinguli
Inferior Frontal Gyrus
Medial Frontal Gyrus
Middle Temporal Gyrus
Occipital Lobe
Occipital Sulcus
Supramarginal Gyrus
Temporal Lobe
Temporal Sulcus
alpha-Synuclein
Aluminum
Amygdaloid Body
APP protein, human
Basal Ganglia
Brain
Brain Stem
Cerebellum
Clone Cells
Cytoskeletal Filaments
Diagnosis
Diencephalon
Entorhinal Area
Eosin
Formaldehyde
Freezing
Gyrus Cinguli
Helix (Snails)
Lewy Body Disease
Locus Coeruleus
Medial Frontal Gyrus
Medulla Oblongata
Mesencephalon
Middle Temporal Gyrus
Neurofibrillary Tangle
Occipital Lobe
Paraffin Embedding
paraform
Parietal Cortex, Inferior
Peptides
Pharmaceutical Preparations
PHF1 protein, human
Pons
Seahorses
Senile Plaques
Silver
Staining
Substantia Nigra
Technique, Dilution
Temporal Lobe
Thalamus
Tissues
Tissue Stains
Most recents protocols related to «Middle Temporal Gyrus»
Using 833 brain tissue samples in the GEO database were analyzed, including 537 AD brain tissue samples and 296 control samples. The expression profiles of the GSE125583, GSE118553, GSE5281, GSE122063, and GSE157239 were download from the GEO database (http://www.ncbi.nlm.nih.gov/geo/ ) (Barrett et al., 2013 (link)). GSE125583 included 219 AD and 70 controls of fusiform gyrus tissue samples, which were obtained based on the GPL16791 platform (Srinivasan et al., 2020 (link)). GSE118553 included 167 AD and 100 controls of the cerebellum, entorhinal cortex, frontal cortex, and temporal cortex tissue samples, which were obtained based on the GPL10558 platform (Patel et al., 2019 (link)). Of these, 134 asymptomatic AD patients were excluded. GSE5281 obtained 87 AD and 74 control brain tissue samples of the following brain regions: the entorhinal cortex, hippocampus, medial temporal gyrus, superior frontal gyrus, posterior cingulate cortex, primary visual cortex, and middle temporal gyrus, based on the GPL570 platform (Liang et al., 2007 (link); Readhead et al., 2018 (link)). GSE122063 was obtained using the GPL16699 platform and included the frontal and temporal cortices from 56 AD and 44 healthy brain tissue samples, while 36 vascular dementia samples were excluded (McKay et al., 2019 (link)). The temporal cortex of eight AD patients and eight controls were obtained from GSE157239, based on the GPL21572 platform.
The expression profile of GSE125583 was normalized using the “Variance Stabilizing Transformation” function of the DESeq2 package. The expression profile of GSE118553 was normalized by “lumiExpresso” function of the Lumi package. The expression profiles of GSE5281 and GSE157239 were normalized using the “RMA” function of Affy package. Moreover, expression profile of GSE122063 was normalized using the limma package.
The expression profile of GSE125583 was normalized using the “Variance Stabilizing Transformation” function of the DESeq2 package. The expression profile of GSE118553 was normalized by “lumiExpresso” function of the Lumi package. The expression profiles of GSE5281 and GSE157239 were normalized using the “RMA” function of Affy package. Moreover, expression profile of GSE122063 was normalized using the limma package.
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Brain
Cerebellum
Dementia, Vascular
Entorhinal Area
Lobe, Frontal
Middle Temporal Gyrus
Occipitotemporal Gyrus, Lateral
Patients
Posterior Cingulate Cortex
Seahorses
Striate Cortex
Superior Frontal Gyrus
Temporal Gyrus
Temporal Lobe
Tissues
Seed-based functional connectivity analysis was used to construct the resting-state cortical visual system. We selected 6 mm radius spheres centered at the right middle occipital gyrus (MNI space: 39 −88 10) [25 (link)], which served as the seed region. The mean time series of the right middle occipital gyrus was computed for each subject as the reference time course for the cortical visual system. Pearson’s cross-correlation analysis was applied to determine the relationship between the seed time course and the time course of all brain voxels, and Fisher’s z-transformation was applied to enhance the normality of the correlation coefficients. This resulted in the generation of a functional connectivity map for each subject. To build the cortical visual system, a one-sample t-test was performed to identify the brain regions that displayed a positive correlation with the right middle occipital gyrus in all subjects.
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Brain
Cortex, Cerebral
Middle Temporal Gyrus
Occipital Gyrus
Radius
Semen Analysis
Visual Cortex
To determine whether the differentially expressed genes in the iPSC-derived neurons capture molecular processes that occur specifically in primary tauopathies or that represent more general pathways associated with neurodegeneration, we analyzed gene expression in human brains with primary tauopathy (e.g., MAPT mutation carriers and progressive supranuclear palsy (PSP)), secondary tauopathy (e.g., Alzheimer disease (AD)), and FTLD with TDP-43 pathology (FTLD-TDP). Primary tauopathy datasets included: i) middle temporal gyrus from MAPT IVS10 + 16 mutation carriers (2 samples) and healthy controls (3 samples); ii) insular cortex from MAPT R406W carriers (2 samples) and healthy controls (2 samples) (Jiang et al., 2018 (link)); and iii) Temporal cortex from progressive supranuclear palsy (PSP) brains (82 samples) and healthy control brains (76 samples; syn6090813) (Allen et al., 2015 (link); Allen et al., 2016 (link)). Secondary tauopathy datasets included temporal cortex from AD brains (84 samples) and healthy controls (76 samples) (Allen et al., 2015 (link); Allen et al., 2016 (link)). To determine whether gene expression changes in iPSC-neuron models reflect a more general impact on neurodegenerative pathways, we examined gene expression profiles isolated from tissue of FTLD-TDP caused by rare mutations the GRN, C9ORF72 expansions, or from sporadic cases (Knight ADRC)(Li et al., 2018 (link); Dube et al., 2019 (link); Wani et al., 2021 (link)): i) parietal lobe from GRN mutation carriers (5 samples), ii) C9ORF72 expansion carriers (5 samples), iii) sporadic cases (8 samples), and (iv) healthy controls (16 samples). Differential gene expression analyses comparing controls and disease diagnosed brains were performed using gene expression measures and including as covariates sex, age-at-death, RNA integrity number (RIN), and brain tissue source.
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Alzheimer's Disease
Brain
Frontotemporal Dementia
Gene Expression
Gene Expression Profiling
Genes
Homo sapiens
Induced Pluripotent Stem Cells
Insula of Reil
MAPT protein, human
Middle Temporal Gyrus
Mutation
Nerve Degeneration
Neurons
Parietal Lobe
Progressive Supranuclear Palsy
Tauopathies
Temporal Lobe
Tissues
Cellular level transcriptomic data from the middle temporal gyrus (MTG) of female and male aged volunteers on the AD spectrum were downloaded from the Seattle Alzheimer’s Disease Brain Cell Atlas (SEA-AD) and was accessed in December 2022 from https://registry.opendata.aws/allen-sea-ad-atlas . Study data were generated from postmortem brain tissue obtained from the MTG of 84 aged individuals spanning the full spectrum of AD severity (preMCI, MCI, mild-moderate severe AD) and 5 neurotypical aged adult cognitively intact individuals.
Adult
Aged
Autopsy
Brain
Brain Diseases
Cells
Females
Gene Expression Profiling
Males
Middle Temporal Gyrus
Tissues
Voluntary Workers
Neuropathological samples with TDP-43 pathology were taken from the Center for Neurodegenerative Disease Research (CNDR) Brain Bank at the University of Pennsylvania, for which the tissue preparation, staining and immunohistochemistry procedures have been described previously24 (link). Both sporadic cases and mutation carriers were included (see Table 1 , S2 ). For each brain, up to 21 regions were sampled comprising the amygdala, hippocampal dentate gyrus, hippocampal cornu ammonis (CA)/subiculum, entorhinal cortex, anterior cingulate, superior/middle temporal gyrus, middle frontal gyrus, angular gyrus, occipital cortex, thalamus, globus pallidus, caudate/putamen, substantia nigra, midbrain, locus coeruleus, upper pons, cerebellum, medulla, orbitofrontal cortex, motor cortex and spinal cord (cervical spinal cord α-motoneurons in lamina 9) (Figure S1 ). Each region was assigned a score according to a semi-quantitative rating scale based on the extent of TDP-43 inclusions, where 0 = non-detectable, 0.5 = sparse, 1 = mild, 2 = moderate, and 3 = severe. The reliability of these scores was verified by independent expert neuropathologists. All individuals with any evidence of TDP-43 pathology in the brain were included in this study.
Three data subsets – those with FTLD-TDP, ALS and LATE-NC – were extracted for disease progression modelling (Table 1 , S2 ). The inclusion criteria for the FTLD-TDP and ALS subsets were a primary neuropathological diagnosis of FTLD-TDP9 (link),25 (link) and ALS12 (link), respectively. Four ALS patients with a diagnosis of “ALS - Other”, which includes ALS without TDP-43 proteinopathy, and one ALS patient with a diagnosis of “ALS - Dementia” were excluded from this study. The inclusion criterion for the LATE-NC subset was a secondary or tertiary neuropathological diagnosis of LATE-NC1 (link), with (LATE-AD+) or without (LATE-AD-) a primary neuropathological diagnosis of Alzheimer’s disease neuropathologic change26 (link). A secondary neuropathological diagnosis of LATE-AD+ was made if individuals showed a primary diagnosis of AD (using NIA-AA criteria), did not have a secondary diagnosis of FTLD or ALS, and also had evidence of TDP-4316 (link). The criteria for a neuropathological diagnosis of LATE-AD- were the absence of another TDP-43 neuropathological diagnosis (i.e. ALS, FTLD-TDP, or corticobasal degeneration), a TDP-43 score of 1 or more in the amygdala, and a TDP-43 score of less than 1 in the medulla (a region with near 100% sampling rate across diagnoses). These inclusion criteria were the sole criteria for inclusion in the study. In particular, we included individuals regardless of their TDP-type (A-E), and mutation carriers (e.g. GRN, C9orf72) and ALS-FTD cases were included. In total there were 126 individuals with FTLD-TDP, 141 with ALS and 304 with LATE-NC that were included in the SuStaIn modelling (Table 1 , S2 ).
Age at death and estimated age at symptom onset were recorded for all individuals. Note that age of symptom onset refers to the age that primary symptoms were reported to manifest, which may or may not be symptoms directly related to TDP-43 neuropathology. Disease duration was calculated as the difference between age at symptom onset and age at death. Sex and interval between death and postmortem examination was also recorded for all patients. APOE genotype (ALS: 99%; FTLD-TDP: 100%; LATE-NC: 98%) and Braak tau stage (ALS: 95%; FTLD-TDP: 99%; LATE-NC: 97%) was also recorded for nearly all individuals using methods that have been previously described24 (link). TDP-43 type was also available for FTLD-TDP patients using published criteria9 (link). TDP-43 type was missing for two FTLD-TDP patients.
Three data subsets – those with FTLD-TDP, ALS and LATE-NC – were extracted for disease progression modelling (
Age at death and estimated age at symptom onset were recorded for all individuals. Note that age of symptom onset refers to the age that primary symptoms were reported to manifest, which may or may not be symptoms directly related to TDP-43 neuropathology. Disease duration was calculated as the difference between age at symptom onset and age at death. Sex and interval between death and postmortem examination was also recorded for all patients. APOE genotype (ALS: 99%; FTLD-TDP: 100%; LATE-NC: 98%) and Braak tau stage (ALS: 95%; FTLD-TDP: 99%; LATE-NC: 97%) was also recorded for nearly all individuals using methods that have been previously described24 (link). TDP-43 type was also available for FTLD-TDP patients using published criteria9 (link). TDP-43 type was missing for two FTLD-TDP patients.
Alzheimer's Disease
Amygdaloid Body
Angular Gyrus
Apolipoproteins E
Autopsy
Brain
Brain Diseases
Cerebellum
Corticobasal Degeneration
Dementia
Diagnosis
Disease Progression
Entorhinal Area
Frontotemporal Dementia
Frontotemporal Lobar Degeneration
Genotype
Globus Pallidus
Gyrus, Anterior Cingulate
Hippocampus Proper
Immunohistochemistry
Inclusion Bodies
Locus Coeruleus
Medial Frontal Gyrus
Medulla Oblongata
Mesencephalon
Middle Temporal Gyrus
Motor Cortex
Motor Neurons
Mutation
Neostriatum
Neuropathologist
Occipital Lobe
Orbitofrontal Cortex
Parahippocampal Gyrus
Patients
Pons
protein TDP-43, human
Spinal Cord
Spinal Cords, Cervical
Subiculum
Substantia Nigra
Superior Temporal Gyrus
TDP-43 Proteinopathies
Thalamus
Tissues
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