A.W. Toga’s research while affiliated with University of Southern California and other places

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Publications (205)


Figure 1 Five main steps of the method for the three modalities used in this study. The data were first acquired from three different databases (Step 1). Then, all neuroimaging data were processed using different software specific to each modality, followed by QC (Step 2). Subsequently, each brain map was parcellated using the Cammoun atlas with 448 cortical regions (Step 3), and the site effect was regressed out using the ComBat software (Step 4). Last, we ensured that each group [participants with an FHAD or with Alzheimer's disease and HCs (when applicable)] had a similar age and men/women proportion at baseline (Step 5).
Figure 2 Brain atrophy progression in individuals with an FHAD and patients with Alzheimer's disease. (A) Baseline atrophy (W-scores with age and sex effects in normal aging regressed out) in FHAD and Alzheimer's disease. (B) Positive and negative β-values associated with higher and lower atrophy progression in FHAD and Alzheimer's disease compared with HCs. Regions with more baseline atrophy overlap with regions with less atrophy progression. (C) Cortical regions showing significant atrophy progression (negative atrophy progression in blue, positive atrophy progression in green) in FHAD and Alzheimer's disease after FDR corrections. Statistical analyses were conducted using linear mixed models with random intercepts and slopes (including group, age, sex, education, BMI, APOe4 status and APOe4 × age interaction as covariates) and post hoc tests. The analyses included data from 153 subjects with FHAD, 156 subjects with Alzheimer's disease and 116 HCs.
Figure 3 Brain atrophy progression in the seven resting-state Yeo networks in individuals with an FHAD and patients with Alzheimer's disease. (A) Positive and negative β-values associated with higher [white area: b-values range = (0-0.002)] and lower [grey area: b-values range = [−0.002 to 0)] atrophy progression in each of the Yeo networks in FHAD and Alzheimer's disease. In Alzheimer's disease, both the limbic network and DMN demonstrated significantly lower atrophy progression compared with HCs. Conversely, the somatosensory network showed an increased rate of atrophy progression. The mean atrophy progression within each network was compared across the three groups (n FHAD = 153, n Alzheimer's disease = 156 and n HC = 116) using linear mixed models with random intercepts and slopes, followed by post hoc tests. Covariates included group, age, sex, education, BMI, APOE4 status and the APOE4 × age interaction. The asterisk (*) indicates statistically significant values (P-value FDR < 0.05). Regions shown correspond to the areas in each of the Yeo networks. (B) Pearson's correlations between average baseline atrophy (W-score) in each of the Yeo networks and the MoCA score, which evaluates general cognitive abilities, in FHAD (n = 128) and Alzheimer's disease (n = 88). Alzheimer's disease participants with higher baseline atrophy in the DA network, FP network and DMN had lower MoCA scores, indicating more cognitive deficits. SM, somatomotor network; VA, ventral attention network.
Figure 5 Relationships with structural connectivity in participants with an FHAD and patients with Alzheimer's disease.
Figure 6 Serotonin and glutamate receptor distribution related to brain atrophy in individuals with an FHAD and Alzheimer's disease. (A) The spatial distribution of the serotonin 5-HT6 receptor (n = 30) in cortical regions (n = 448) was negatively correlated with atrophy progression in both FHAD (n Baseline = 153) and Alzheimer's disease (n Baseline = 156) but was only significant in Alzheimer's disease after comparison with a spatial null distribution and FDR correction. (B) Positive and significant correlations were observed between the serotonin 5-HT6 receptor distribution (n = 30) and baseline atrophy (n FHAD = 153, n Alzheimer's disease = 156) in both groups, suggesting that the negative correlations most likely reflect a ceiling effect. In addition, the distribution of the serotonin 5-HT1B receptor (n = 88) was significantly correlated with baseline atrophy, but only in FHAD. Finally, significant correlations were observed between the metabotropic glutamate receptor 5 (mGluR5) distribution (n = 123) and baseline atrophy (n FHAD = 153, n Alzheimer's disease = 156) in both groups. All correlations were spatial Pearson's correlations performed across 448 cortical regions. The dots represent the spatial correlation coefficients for each group, while the asterisks (*) indicate statistically significant values after comparison with a spatial null distribution and FDR correction (1000 spins, P-value spin-FDR < 0.05).

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Uncovering atrophy progression pattern and mechanisms in individuals at risk of Alzheimer’s disease
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March 2025

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192 Reads

Brain Communications

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Alexandre Pastor Bernier

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Alzheimer’s disease (AD) is associated with presymptomatic changes in brain morphometry and accumulation of abnormal tau and amyloid-beta pathology. Studying the development of brain changes prior to symptoms onset may lead to early diagnostic biomarkers and a better understanding of AD pathophysiology. AD pathology is thought to arise from a combination of protein accumulation and spreading via neural connections, but how these processes influence brain atrophy progression in the presymptomatic phases remains unclear. Individuals with a family history of AD (FHAD) have an elevated risk of AD, providing an opportunity to study the presymptomatic phase. Here we used structural MRI from three databases (Alzheimer’s Disease Neuroimaging Initiative, Pre-symptomatic Evaluation of Experimental or Novel Treatments for Alzheimer Disease and Montreal Adult Lifespan Study) to map atrophy progression in FHAD and AD and assess the constraining effects of structural connectivity on atrophy progression. Cross-sectional and longitudinal data up to four years were used to perform atrophy progression analysis in FHAD and AD compared to controls. Positron emission tomography radiotracers were also used to quantify the distribution of abnormal tau and amyloid-beta protein isoforms at baseline. We first derived cortical atrophy progression maps using deformation-based morphometry from 153 FHAD, 156 AD, and 116 controls with similar age, education, and sex at baseline. We next examined the spatial relationship between atrophy progression and spatial patterns of tau aggregates and amyloid-beta plaques deposition, structural connectivity, and neurotransmitter receptor and transporter distributions. Our results show that there were similar patterns of atrophy progression in FHAD and AD, notably in the cingulate, temporal, and parietal cortices, with more widespread and severe atrophy in AD. Both tau and amyloid-beta pathology tended to accumulate in regions that were structurally connected in FHAD and AD. The pattern of atrophy and its progression also aligned with existing structural connectivity in FHAD. In AD, our findings suggest that atrophy progression results from pathology propagation that occurred earlier, on a previously intact connectome. Moreover, a relationship was found between serotonin receptor spatial distribution and atrophy progression in AD. The current study demonstrates that regions showing atrophy progression in FHAD and AD present with specific connectivity and cellular characteristics, uncovering some of the mechanisms involved in preclinical and clinical neurodegeneration.

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Fig. 1 ADNI polygenic risk score distributions. Alzheimer's disease polygenic risk score distributions are shown for a ADNI participants with a CDR ≥ 1 compared to ADNI participants with a CDR ≤ 0.5 and b ADNI participants with a CDR ≥ 0.5 compared to ADNI participants with a CDR = 0.
Fig. 2 ADNI Polygenic Risk Scores using Lambert et al., 2013 GWA Summary Statistics. PRSice-2 (dark grey), and the PRSKB (light grey) scores are shown. a PRSice-2 reports polygenic risk scores that center on 0, so 1.0 was added to each PRSice-2 score to put it on the same scale as the PRSKB, which centers polygenic risk scores based on odds ratios around 1.0. The PRSice-2 median score after transformation is 1.05207 and the PRSKB median score is 1.05338. b Since a polygenic risk score is a relative score compared to the sample population, we transformed the PRSKB scores by subtracting 0.00131 to overlap the shape of the distributions when both algorithms report the same median. Since the scores are normally distributed, a Welch's two-sample t-test was used to determine the similarity between the two distributions, which were nearly identical (t = 0.004782; P = 0.9962).
The Polygenic Risk Score Knowledge Base offers a centralized online repository for calculating and contextualizing polygenic risk scores

September 2022

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349 Reads

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11 Citations

Communications Biology

The process of identifying suitable genome-wide association (GWA) studies and formatting the data to calculate multiple polygenic risk scores on a single genome can be laborious. Here, we present a centralized polygenic risk score calculator currently containing over 250,000 genetic variant associations from the NHGRI-EBI GWAS Catalog for users to easily calculate sample-specific polygenic risk scores with comparable results to other available tools. Polygenic risk scores are calculated either online through the Polygenic Risk Score Knowledge Base (PRSKB; https://prs.byu.edu ) or via a command-line interface. We report study-specific polygenic risk scores across the UK Biobank, 1000 Genomes, and the Alzheimer’s Disease Neuroimaging Initiative (ADNI), contextualize computed scores, and identify potentially confounding genetic risk factors in ADNI. We introduce a streamlined analysis tool and web interface to calculate and contextualize polygenic risk scores across various studies, which we anticipate will facilitate a wider adaptation of polygenic risk scores in future disease research.


How Will Aducanumab Approval Impact AD Research?

September 2021

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40 Reads

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9 Citations

The Journal of Prevention of Alzheimer s Disease

The accelerated approval of aducanumab (AduhelmTM) by the US FDA is a momentous event. For the first time, a therapeutic agent that targets the neurobiology of Alzheimer’s disease (AD) is available for clinical use (1, 2). In addition to the FDA approval of aducanumab, the FDA has also provided “Breakthrough therapy designation” for Lilly’s Donanemab and Eisai’s Lecnemab which also are monoclonal antibodies that remove brain amyloid plaques and may slow cognitive decline. Aducanumab approval will impact clinical practice. The effects on AD clinical research will be profound in both positive and negative ways. This Editorial reflects the opinion of the leadership of the Alzheimer’s Disease Neuroimaging Initiative (ADNI), a large multisite longitudinal observational study with the goal of validating biomarkers for clinical trials. ADNI data have been used to help design and statistically power many AD clinical trials, including the aducanumab studies.


Genetic architecture of subcortical brain structures in 38,851 individuals

November 2019

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142 Reads

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68 Citations

Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.


Non-coding variability at the APOE locus contributes to the Alzheimer's risk

July 2019

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161 Reads

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48 Citations

Nature Communications

Alzheimer’s disease (AD) is a leading cause of mortality in the elderly. While the coding change of APOE-ε4 is a key risk factor for late-onset AD and has been believed to be the only risk factor in the APOE locus, it does not fully explain the risk effect conferred by the locus. Here, we report the identification of AD causal variants in PVRL2 and APOC1 regions in proximity to APOE and define common risk haplotypes independent of APOE-ε4 coding change. These risk haplotypes are associated with changes of AD-related endophenotypes including cognitive performance, and altered expression of APOE and its nearby genes in the human brain and blood. High-throughput genome-wide chromosome conformation capture analysis further supports the roles of these risk haplotypes in modulating chromatin states and gene expression in the brain. Our findings provide compelling evidence for additional risk factors in the APOE locus that contribute to AD pathogenesis.


Exploration of Shared Genetic Architecture Between Subcortical Brain Volumes and Anorexia Nervosa

July 2019

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293 Reads

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4 Citations

Molecular Neurobiology

In MRI scans of patients with anorexia nervosa (AN), reductions in brain volume are often apparent. However, it is unknown whether such brain abnormalities are influenced by genetic determinants that partially overlap with those underlying AN. Here, we used a battery of methods (LD score regression, genetic risk scores, sign test, SNP effect concordance analysis, and Mendelian randomization) to investigate the genetic covariation between subcortical brain volumes and risk for AN based on summary measures retrieved from genome-wide association studies of regional brain volumes (ENIGMA consortium, n = 13,170) and genetic risk for AN (PGC-ED consortium, n = 14,477). Genetic correlations ranged from − 0.10 to 0.23 (all p > 0.05). There were some signs of an inverse concordance between greater thalamus volume and risk for AN (permuted p = 0.009, 95% CI: [0.005, 0.017]). A genetic variant in the vicinity of ZW10, a gene involved in cell division, and neurotransmitter and immune system relevant genes, in particular DRD2, was significantly associated with AN only after conditioning on its association with caudate volume (pFDR = 0.025). Another genetic variant linked to LRRC4C, important in axonal and synaptic development, reached significance after conditioning on hippocampal volume (pFDR = 0.021). In this comprehensive set of analyses and based on the largest available sample sizes to date, there was weak evidence for associations between risk for AN and risk for abnormal subcortical brain volumes at a global level (that is, common variant genetic architecture), but suggestive evidence for effects of single genetic markers. Highly powered multimodal brain- and disorder-related genome-wide studies are needed to further dissect the shared genetic influences on brain structure and risk for AN.


Novel genetic loci underlying human intracranial volume identified through genome-wide association

December 2016

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452 Reads

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156 Citations

Nature Neuroscience

Intracranial volume reflects the maximally attained brain size during development, and remains stable with loss of tissue in late life. It is highly heritable, but the underlying genes remain largely undetermined. In a genome-wide association study of 32,438 adults, we discovered five novel loci for intracranial volume and confirmed two known signals. Four of the loci are also associated with adult human stature, but these remained associated with intracranial volume after adjusting for height. We found a high genetic correlation with child head circumference (ρgenetic=0.748), which indicated a similar genetic background and allowed for the identification of four additional loci through meta-analysis (Ncombined = 37,345). Variants for intracranial volume were also related to childhood and adult cognitive function, Parkinson’s disease, and enriched near genes involved in growth pathways including PI3K–AKT signaling. These findings identify biological underpinnings of intracranial volume and provide genetic support for theories on brain reserve and brain overgrowth.


FIG 1. Relationship between obesity and physical activity on brain structure (adapted with per- mission from Boyle et al 23 ). The top panel shows whole-brain 3D maps in which regional brain 
Hot Topics in Research: Preventive Neuroradiology in Brain Aging and Cognitive Decline

June 2015

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243 Reads

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15 Citations

American Journal of Neuroradiology

Preventive neuroradiology is a new concept supported by growing literature. The main rationale of preventive neuroradiology is the application of multimodal brain imaging toward early and subclinical detection of brain disease and subsequent preventive actions through identification of modifiable risk factors. An insightful example of this is in the area of age-related cognitive decline, mild cognitive impairment, and dementia with potentially modifiable risk factors such as obesity, diet, sleep, hypertension, diabetes, depression, supplementation, smoking, and physical activity. In studying this link between lifestyle and cognitive decline, brain imaging markers may be instrumental as quantitative measures or even indicators of early disease. The purpose of this article is to provide an overview of the major studies reflecting how lifestyle factors affect the brain and cognition aging. In this hot topics review, we will specifically focus on obesity and physical activity. © 2015 American Society of Neuroradiology.



Figure 1. Genomic and linkage disequilibrium (LD) structure of CREB1 as well as association results with bipolar disorder. The results in the discovery sample were shown in red circle, and the results in the replication sample were shown in blue square, and the results in the combined sample were shown in green triangle. The LD color scheme was defined using the R-squared and the LD value of the paired SNPs was calculated using the r 2 algorithm. The r 2 value for each color was: black ( r 2 4 0.90), dark gray (0.2 o r 2 o 0.6), gray (0.01 p r 2 o 0.2), white ( r 2 p 0.01). 
Table 1 . Nucleotide diversity and neutrality tests for CREB1 and three neighboring genes in human populations
Figure 2. Effect of the risk single-nucleotide polymorphism (SNP) rs2709370 on hippocampal function. During memory recall, carriers of the risk allele (C) of rs2709370 exhibit significantly decreased allele-dosage-dependent hippocampal activation in the left hippocampus ( Z 1⁄4 3.97, P o 0.01, family wise error corrected for multiple testing across region of interest). Each red dot represents size of effect in one subject and reflects hippocampal activation. Number of subjects in each group: CC 1⁄4 14, AC 1⁄4 99, AA 1⁄4 166. 
Figure 3. Effects of risk single-nucleotide polymorphisms (SNPs) on CREB1 mRNA expression. (a) Results in the lymphoblastoid cell lines of 75 healthy European subjects. (b) Results in the prefrontal cortex of healthy Caucasian and African-American subjects (N ¼ 261).
Figure 4. Global distribution of CREB1 single-nucleotide polymorphisms (SNPs) in world populations. ( a ) Global distribution of rs6785 (risk SNP) allele frequencies in world populations. The derived allele [A] is the risk allele. ( b ) Global distribution of rs2254137 (non-risk SNP) allele frequencies in world populations. 
Allelic differences between Europeans and Chinese for CREB1 SNPs and their implications in gene expression regulation, hippocampal structure and function, and bipolar disorder susceptibility

April 2013

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207 Reads

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69 Citations

Molecular Psychiatry

Bipolar disorder (BD) is a polygenic disorder that shares substantial genetic risk factors with major depressive disorder (MDD). Genetic analyses have reported numerous BD susceptibility genes, while some variants, such as single-nucleotide polymorphisms (SNPs) in CACNA1C have been successfully replicated, many others have not and subsequently their effects on the intermediate phenotypes cannot be verified. Here, we studied the MDD-related gene CREB1 in a set of independent BD sample groups of European ancestry (a total of 64 888 subjects) and identified multiple SNPs significantly associated with BD (the most significant being SNP rs6785[A], P=6.32 × 10(-5), odds ratio (OR)=1.090). Risk SNPs were then subjected to further analyses in healthy Europeans for intermediate phenotypes of BD, including hippocampal volume, hippocampal function and cognitive performance. Our results showed that the risk SNPs were significantly associated with hippocampal volume and hippocampal function, with the risk alleles showing a decreased hippocampal volume and diminished activation of the left hippocampus, adding further evidence for their involvement in BD susceptibility. We also found the risk SNPs were strongly associated with CREB1 expression in lymphoblastoid cells (P<0.005) and the prefrontal cortex (P<1.0 × 10(-6)). Remarkably, population genetic analysis indicated that CREB1 displayed striking differences in allele frequencies between continental populations, and the risk alleles were completely absent in East Asian populations. We demonstrated that the regional prevalence of the CREB1 risk alleles in Europeans is likely caused by genetic hitchhiking due to natural selection acting on a nearby gene. Our results suggest that differential population histories due to natural selection on regional populations may lead to genetic heterogeneity of susceptibility to complex diseases, such as BD, and explain inconsistencies in detecting the genetic markers of these diseases among different ethnic populations.Molecular Psychiatry advance online publication, 9 April 2013; doi:10.1038/mp.2013.37.


Citations (59)


... The development and construction of PGS/PRS have been the focus of many methodological studies, and these studies have provided effective tools for constructing reliable PGS/PRS [15,[17][18][19]. These tools allow PGS/PRS to be derived from very large data sets or meta-analyses [20][21][22], and open-source websites have been developed that provide the information needed to compute PRS for over 3200 traits and diseases [13,23]. The ubiquity of PGS/PRS methods and the availability of large data sets have motivated studies of the polygenic basis of many nondisease traits, such as height [24], as well as healthpositive traits such as health span [25], beneficial disease treatment response [26][27][28], and resilience to disease and longevity [29][30][31][32][33][34]. ...

Reference:

The relationship between 11 different polygenic longevity scores, parental lifespan, and disease diagnosis in the UK Biobank
The Polygenic Risk Score Knowledge Base offers a centralized online repository for calculating and contextualizing polygenic risk scores

Communications Biology

... For example, the third phase of the initiative has recruited an additional 1200 volunteers to donate their data, to assess cognitive function through computer tests at home and in the clinic measuring changes in ability to handle money, and early signs of the disease. 30,31 Years of research, progress of establishing validation, and POC for beta amyloid PET imaging took place under the umbrella of the ADNI. 32 Recently, the FDA has rendered beta-amyloid PET as a reasonably likely surrogate of cognitive decline, based on analysis of publicly available neuroimaging data and clinical outcomes from multiple independent trials which tested drug candidates targeting beta amyloid. ...

How Will Aducanumab Approval Impact AD Research?

The Journal of Prevention of Alzheimer s Disease

... Standard GWAS QC was previously performed on the PRS-CS reference panel which overlapped with 1,062,342 SNPs for CUD, 1,060,634 SNPs for cortical surface area, 1,061,323 SNPs for cortical thickness, 1,042,513 SNPs for brainstem, 1,056,811 for hippocampus, 1,042,259 for nucleus accumbens, 1,039,048 for putamen, 1,038,846 for caudate, 1,041,942 for thalamus. PRSs were estimated for: a general addiction factor (Hatoum et al., 2023); cannabis use disorder (Johnson et al., 2020); cortical surface area and cortical thickness (Grasby et al., 2020); hippocampus, nucleus accumbens, caudate nucleus, putamen and thalamus (Satizabal et al., 2019). Each set of summary statistics was checked for duplicates, and 17 duplicate SNPs were found in the thalamus summary statistics. ...

Genetic architecture of subcortical brain structures in 38,851 individuals
  • Citing Article
  • November 2019

... 33 Together, APOE, APOC1, and NECTIN2 haplotypes confirm a risk of AD over and above APOE. 34 In chromosome 19, our results suggested only rs429358 as a putative causal SNP, indicating the importance of the APOE gene for plasma p-tau217 levels. In addition, we found two putative causal SNPs, rs9402117 and rs115553322, in chromosomes 6 and 11, respectively, but these have not been indicated earlier to be associated with AD or dementia, and no genes in these chromosomes were implicated in the gene-based analyses. ...

Non-coding variability at the APOE locus contributes to the Alzheimer's risk
  • Citing Article
  • July 2019

Nature Communications

... FABP-5 (epidermal-FABP) has been implicated in hippocampal-based learning and memory, 60 as well as brain uptake of docosahexaenoic acid. 61 Serum FABP-7 (brain-FABP) levels are reportedly increased in Parkinson's and Alzheimer's disease. 62 Serum FABP-3 (heart-FABP) has been found increased in patients with Lewy-body dementia 63 and Parkinson's disease with dementia 64 ; and was suggested as a marker discriminating Alzheimer's disease in Mexican Americans. ...

Novel genetic loci underlying human intracranial volume identified through genome-wide association

Nature Neuroscience

... The present study uses a computational anatomy shape-based method called hippocampal radial distance in order to compare cross-sectional 3D hippocampal maps of subjects diagnosed with dementia and normal controls. This technique allows for detection of subtler hippocampal shape changes in AD (Apostolova et al., 2006a;Apostolova et al., 2006c;Apostolova et al., 2012;Apostolova et al., 2010b;Frisoni et al., 2006;Thompson et al., 2004). The hippocampal radial distance approach relies on manual or automated hippocampal segmentations, which are converted into 3D anatomical mesh models for each subject. ...

Erratum: 3D comparison of hippocampal atrophy in amnestic mild cognitive impairment and Alzheimer's disease (Brain (2006) 127, part 11, (2867-2873) DOI: 10.1093/brain/awl274)
  • Citing Article
  • September 2007

Brain

... However, there is large heterogeneity among meditation techniques, which often involve very different practices and which are likely to have different effects on the brain. So far, the following meditation techniques have been studied using brain structure imaging techniques: Zen meditation [23,27], Tibetan Buddhist meditation [22], Mindfulness meditation [25,28,29], Soham [30], Loving-kindness meditation [21], Brain wave vibration [18], or a combination of different meditation techniques within the same study: Chenrezig-Kriya-Shamatha-Vajrayana-Vipassana and Zazen [17,20,26,[31][32][33]. ...

The unique anatomy of the hippocampus in meditation practitioners
  • Citing Conference Paper
  • September 2012

European Journal of Neurology

... The brain's most prominent structural asymmetry is the Yakovlevian torque-a forward warp of the right hemisphere and a backward warp of the left hemisphere (Kong et al., 2021;LeMay, 1976). However, several other left-right differences exist, as summarized elsewhere (Jancke, 2003;Toga et al., 2009). For example, the left Sylvian fissure is often longer and runs more horizontally than the right, whereas the left hemisphere often contains only one Heschl's gyrus, but the right hemisphere contains two. ...

Brain Asymmetry: Evolution
  • Citing Article
  • January 2010

... At present, the cognitive psychology technology applied to study the cognitive function is mainly in the memory field [1]. Through the experimental studies of cognitive function, we have gradually explored the mechanisms of cognitive decline [2]. In life, people sometimes falsely recall events that never happened, or recall events that were not exactly the same as their actual experiences. ...

Hot Topics in Research: Preventive Neuroradiology in Brain Aging and Cognitive Decline

American Journal of Neuroradiology

... Pearson correlation coefficient was used to establish interrelationships between variables. Partial correlations were used to control for the interdependence of different brain volumes within subjects, as has been proposed and used for structural brain data [51][52][53] . The correlation values with brain structural parameters were corrected by the false discovery rate (FDR, q < 0.05). ...

Anatomical structural network analysis of human brain using partial correlations of gray matter volumes
  • Citing Conference Paper
  • January 2010

Proceedings / IEEE International Symposium on Biomedical Imaging: from nano to macro. IEEE International Symposium on Biomedical Imaging