Biomedical subjects

Anders M Dale

Publications and source records attributed to Anders M Dale.

At least 19 recordsLinked to original sources

PubMed2026

Beyond exons: Linking noncoding heritability and polygenicity across complex human traits and disorders.

The genetic architecture of complex traits spans a continuum of polygenicity, yet it remains unclear how differences in polygenicity relate to the functional localization of SNP heritability across the genome. We use a MiXeR-based framework to partition heritability across 74 functional annotations covering exonic, intronic, and intergenic regions for 34 complex traits and introduce a likelihood-based annotation contribution score that quantifies annotation-specific impact on heritability. Exons account for a minority of heritability, and their contribution decreases with increasing polygenicity, from an average of 22% in less-polygenic somatic diseases and biomarkers to 13% in highly polygenic psychiatric and cognitive phenotypes. Intergenic fractions show the opposite trend, whereas intronic fractions remain relatively stable. Analysis of the broader set of functional annotations also reveals systematic differences along the polygenicity axis: highly polygenic traits show stronger contributions from comparative genomics and variant-effect scores, whereas less-polygenic traits show stronger contributions from promoter, transcription, and chromatin annotations. Together, these results indicate that the functional partitioning of heritability systematically varies with polygenicity, shifting from gene-proximal regulatory architectures to architectures shaped by numerous dispersed regulatory effects.

MiXeR↗

PubMed2026

Genomic dimensions deconstruct the clinical heterogeneity of bipolar disorder.

Bipolar disorder's (BD) clinical heterogeneity has an unresolved genetic basis. We meta-analyzed genome-wide association studies (GWAS) of 16 BD subphenotypes in 226,032 individuals from 57 cohorts (38,022 cases); 10 advanced to multivariate and multi-trait analyses. Four factors (compulsive, psychotic, dysregulated, internalizing) explained 82.8% of shared genetic variance. BD1 and BD2 loaded on distinct factors despite a high genetic correlation; 87.0% of common-factor loci were significant in neither subtype. Unipolar mania aligned with psychosis over internalizing, and was distinguishable from BD1, and rapid cycling showed heritable cross-domain liability. We identified 356 risk loci, 158 novel, including the first univariate-GWAS associations for psychosis, unipolar mania, rapid cycling and schizoaffective disorder-and 249 credible genes (89 high-confidence), 12 with approved-drug or clinical-phase annotations. Cell-type association showed a midbrain dopaminergic-GABAergic gradient along the psychotic factor. BD's genetic architecture appears hierarchical-a general liability resolving into dimensions of course and comorbidity, beyond subtypes.

Journal Article↗

PubMed2026

Genomic relationship between polyendocrine metabolic ovarian syndrome and bipolar disorder.

Women with bipolar disorder (BIP) have a higher risk of developing polyendocrine metabolic ovarian syndrome (PMOS). Shared genetic architecture may underlie this comorbidity. Valproate, a mood-stabilizer commonly used to treat BIP, increases the risk of PMOS. Still, the mechanism underlying PMOS in BIP remains unknown. Here, we aimed to identify genetic variants shared between BIP and PMOS, as well as their interaction with valproate. We used the results of large-scale genome-wide association studies of BIP (41,510 cases and 354,340 controls), and PMOS (3609 cases and 229,788 controls). Using conditional false discovery rate, we discovered genetic variants jointly associated with BIP and PMOS. Gene mapping of identified variants was performed using the Open Targets platforms. We analyzed the tissue-specific expression, interaction with valproate, and involvement in biological pathways of the mapped genes. We identified two loci shared between BIP and PMOS. Among the 10 genes mapped to the locus on chromosome 8:11,444,837-11,463,015, GATA4, NEIL2, and FDFT1 showed expression profiles suggesting their role in the observed comorbidity. Mapped to the locus on chromosome 12:2499,849-2514,270, CACNA1C, FKBP4, DCP1B, and ITFG2 are expressed in both the ovaries and the brain. Valproate interacts with CACNA1C, and CACNA1C is part of biological pathways that also include other genes interacting with valproate. We identified shared genetic underpinnings of BIP and PMOS and highlighted genes that may potentially contribute to the biological mechanisms underlying their comorbidity and to a hypothesized role of valproate in these mechanisms.

Female↗

PubMed2026

Beyond Exons: Linking Noncoding Heritability and Polygenicity across Complex Human Traits and Disorders.

The genetic architecture of complex traits spans a continuum of polygenicity, yet it remains unclear how differences in polygenicity relate to the functional localization of SNP heritability across the genome. We use a MiXeR-based framework to partition heritability across exonic, intronic, and intergenic regions for 34 traits and introduce a likelihood-based annotation contribution score that quantifies annotation-specific impact on heritability. Exons explain a minority of heritability, and their contribution decreases with increasing polygenicity, from an average of 22% in less polygenic somatic diseases and biomarkers to 13% in highly polygenic psychiatric and cognitive phenotypes. Intergenic fractions show the opposite trend, whereas intronic fractions remain relatively stable. Analysis of a broader set of functional annotations reveals systematic differences along the polygenicity axis: highly polygenic traits show stronger contributions from comparative genomics and variant-effect scores, whereas less polygenic traits show stronger contributions in promoter, transcription, and chromatin annotations. Together, these results indicate that the functional partitioning of heritability systematically varies with polygenicity, pointing to a shift from gene-proximal regulatory architectures to architectures shaped by numerous dispersed regulatory effects as a key determinant of differences in polygenicity across traits.

Journal Article↗

PubMed2026

Leveraging the genetics of psychiatric disorders to prioritize potential drug targets and compounds.

Genetics can inform biologically relevant drug development and repurposing, which may improve patient care. Here, we leverage the genetics of psychiatric disorders to prioritize potential drug targets and compounds. We used the genome-wide association studies of four psychiatric disorders [attention deficit hyperactivity disorder (ADHD), bipolar disorder, depression, and schizophrenia] and genes encoding drug targets. We conducted drug enrichment analyses incorporating the novel and biologically specific GSA-MiXeR tool. We conducted multiple molecular trait analyses using large-scale transcriptomic and proteomic datasets sampled from brain and blood tissue. This included the novel use of the UK Biobank proteomic data for a proteome-wide association study of psychiatric disorders. With the accumulated evidence, we prioritize potential drug targets and compounds for each disorder. We reveal candidate drug targets associated with a single or multiple disorders that implicate glutamate signaling. Drug prioritization indicated genetic support for psychotropic medications, including several top-ranked antipsychotics for schizophrenia. We also observed genetic support for commonly used psychotropics for psychiatric treatment (e.g., clozapine, duloxetine, and lithium). Revealed opportunities for drug repurposing included cholinergic drugs for ADHD, estrogen modulators for depression, and matrix metalloproteinases for ADHD and depression. Our findings indicate the genetic liability to schizophrenia is associated with reduced brain and blood expression of CYP2D6, a gene encoding a metabolizer of drugs and neurotransmitters, suggesting a genetic risk for poor drug response and altered neurotransmission. Our extensive analyses highlight the utility of genetics for informing drug development and repurposing for psychiatric disorders, providing novel opportunities for improving patient outcomes. Depicted is the series of analyses conducted to generate a list of prioritized drug targets and compounds. First pairings of genome-wide association study (GWAS) traits with drugs are generated using enrichment analyses. Next, a series of molecular trait analyses is conducted to generate and rank a list of potential drug targets for each GWAS trait. Finally, enrichment and molecular trait results are combined to generate a ranked list of prioritized drugs for each GWAS trait based on supporting genetic evidence. ADHD = Attention deficit hyperactivity disorder, BIP = Bipolar disorder, DEP = Depression, SCZ = Schizophrenia, DBP = Diastolic blood pressure, T2D = Type 2 diabetes, RNA = ribonucleic acid, XWAS = both transcriptome and proteome-wide association studies, MR = Mendelian randomization, coloc = colocalization.

Humans↗

PubMed2025

A genome-wide analysis of the shared genetic risk architecture of complex neurological and psychiatric disorders.

Although neurological and psychiatric disorders have historically been considered to reflect distinct pathogenic entities, recent findings suggest shared pathophysiological mechanisms. However, the extent to which these heritable disorders share genetic influences remains unclear. Here we performed a comprehensive analysis of genome-wide association study data, involving nearly 1 million cases across ten neurological diseases and ten psychiatric disorders, to compare their common genetic signal and biological associations. Using complementary statistical tools, we demonstrate that a large set of common genetic variants impacts the risk of multiple neurological and psychiatric disorders, even in the absence of genetic correlations. Furthermore, genome-wide association studies on psychiatric disorders consistently implicate neuronal biology, whereas neurological diseases are associated with diverse neurobiological processes. Together, this study elucidates the genetic relationship between complex neurological and psychiatric disorders, indicating a larger degree of genetic pleiotropy than previously recognized. The findings have implications for disease classification, precision medicine and clinical practice.

Humans↗

PubMed2025

Genomic relationship between polycystic ovary syndrome and bipolar disorder.

Women with bipolar disorder (BIP) have a higher risk of developing polycystic ovary syndrome (PCOS). Shared genetic architecture may underlie this comorbidity. Valproate, a mood-stabilizer commonly used to treat BIP, increases the risk of PCOS. Still, the mechanism underlying PCOS in BIP remains unknown. Here, we aimed to identify genetic variants shared between BIP and PCOS, as well as their interaction with valproate. We used the results of large-scale genome-wide association studies of BIP (41,510 cases and 354,340 controls), and PCOS (3,609 cases and 229,788 controls). Using conditional false discovery rate, we discovered genetic variants jointly associated with BIP and PCOS. Gene mapping of identified variants was performed using the Open Targets platforms. We analyzed the tissue-specific expression, interaction with valproate, and involvement in biological pathways of the mapped genes. We identified two loci shared between BIP and PCOS. Among the 10 genes mapped to the locus on chromosome 8:11455262, GATA4, NEIL2, and FDFT1 showed expression profiles suggesting their role in the observed comorbidity. Mapped to the locus on chromosome 12:2499849, CACNA1C, FKBP4, DCP1B, and ITFG2 are expressed in both the ovaries and the brain. CACNA1C expression is affected by valproate, and CACNA1C plays a role in biological pathways involving other valproate-affected genes. We identified shared genetic underpinnings of BIP and PCOS, and implicated genes which may explain the biological mechanisms of the comorbidity between these disorders and a potential mechanism for the role of valproate.

bipolar disorder↗

PubMed2025

Comorbidity alters the genetic relationship between anxiety disorders and major depression.

BACKGROUND: Comorbid anxiety disorders (ANX) and major depression (MD) have worse clinical outcomes than either disorder alone. Analysis of genomic data based on comorbidity status may reveal more precise biological pathways and causal relationships with potential clinical implications. We investigated the genetic relationship between ANX and MD with and without mutual comorbidity. METHODS: We leveraged data from UK Biobank to perform disorder-specific genome-wide association studies (GWAS) of ANX-only (n=189,422) and MD-only (n=194,339) and generate polygenic risk scores (PRS). The Norwegian Mother, Father, and Child Cohort (MoBa, n = 130,992) served to test the associations of PRS with diagnoses. MD and ANX GWAS, including comorbidities (MD-comorbid and ANX-comorbid), were used for comparison. Genetic correlations were compared by comorbidity status, and Mendelian randomization was employed to assess causal relationships. RESULTS: The MD-only PRS showed a stronger association with MD-only compared to ANX-only cases (Z=3.74; Padjusted=0.002); however, MD-comorbid PRS did not show a significant difference (Z=2.71; Padjusted=0.08). The genetic correlation between ANX-only and MD-only was 0.53, lower than between ANX-comorbid and MD-comorbid (0.90). ANX-only showed a causal relationship with MD-only (Padjusted=0.015), but not vice versa, and contrasted the bidirectional causal relationship (Padjusted=2.9e-12, and Padjusted=9.3e-06) when comorbidity was included. Gene sets of MD-comorbid, ANX-comorbid, and MD-only, but not of ANX-only, were enriched for immune regulation pathways such as interleukin production. CONCLUSIONS: ANX and MD show more distinct genetics when comorbid cases are excluded, and ANX may be causal for MD. Disorder-specific genetic studies help uncover more relevant biological mechanisms and guide tailored clinical interventions.

Journal Article↗

PubMed2021

1q21.1 distal copy number variants are associated with cerebral and cognitive alterations in humans.

Low-frequency 1q21.1 distal deletion and duplication copy number variant (CNV) carriers are predisposed to multiple neurodevelopmental disorders, including schizophrenia, autism and intellectual disability. Human carriers display a high prevalence of micro- and macrocephaly in deletion and duplication carriers, respectively. The underlying brain structural diversity remains largely unknown. We systematically called CNVs in 38 cohorts from the large-scale ENIGMA-CNV collaboration and the UK Biobank and identified 28 1q21.1 distal deletion and 22 duplication carriers and 37,088 non-carriers (48% male) derived from 15 distinct magnetic resonance imaging scanner sites. With standardized methods, we compared subcortical and cortical brain measures (all) and cognitive performance (UK Biobank only) between carrier groups also testing for mediation of brain structure on cognition. We identified positive dosage effects of copy number on intracranial volume (ICV) and total cortical surface area, with the largest effects in frontal and cingulate cortices, and negative dosage effects on caudate and hippocampal volumes. The carriers displayed distinct cognitive deficit profiles in cognitive tasks from the UK Biobank with intermediate decreases in duplication carriers and somewhat larger in deletion carriers-the latter potentially mediated by ICV or cortical surface area. These results shed light on pathobiological mechanisms of neurodevelopmental disorders, by demonstrating gene dose effect on specific brain structures and effect on cognitive function.

Brain↗

PubMed2007

Depth-resolved optical imaging and microscopy of vascular compartment dynamics during somatosensory stimulation.

The cortical hemodynamic response to somatosensory stimulus is investigated at the level of individual vascular compartments using both depth-resolved optical imaging and in-vivo two-photon microscopy. We utilize a new imaging and spatiotemporal analysis approach that exploits the different characteristic dynamics of responding arteries, arterioles, capillaries and veins to isolate their three-dimensional spatial extent within the cortex. This spatial delineation is validated using vascular casts. Temporal delineation is supported by in-vivo two-photon microscopy of the temporal dynamics and vascular mechanisms of the arteriolar and venous responses. Using these techniques we have been able to characterize the roles of the different vascular compartments in generating and controlling the hemodynamic response to somatosensory stimulus. We find that changes in arteriolar total hemoglobin concentration agree well with arteriolar dilation dynamics, which in turn correspond closely with changes in venous blood flow. For 4-s stimuli, we see only small changes in venous hemoglobin concentration, and do not detect measurable dilation or ballooning in the veins. Instead, we see significant evidence of capillary hyperemia. We compare our findings to historical observations of the composite hemodynamic response from other modalities including functional magnetic resonance imaging. Implications of our results are discussed with respect to mathematical models of cortical hemodynamics, and to current theories on the mechanisms underlying neurovascular coupling. We also conclude that our spatiotemporal analysis approach is capable of isolating and localizing signals from the capillary bed local to neuronal activation, and holds promise for improving the specificity of other hemodynamic imaging modalities.

Animals↗

PubMed2007

Spatiotemporal cortical dynamics underlying abstract and concrete word reading.

The current study used whole-head anatomically constrained magnetoencephalography (aMEG) to spatiotemporally map brain responses while subjects made abstract/concrete judgments on visually presented words. Both word types evoked a similar posterior-to-anterior sequence of cortical recruitment involving occipital, temporal, parietal, and frontal areas from approximately 100 to 900 ms poststimulus. A prominent left temporofrontal N400m was smaller to abstract words, while the right temporal N400m was smaller to concrete words, suggesting that differences may exist in their semantic representation. The left temporofrontal decrease for abstract words is consistent with EEG studies, indicating a smaller N400 for abstract words based on a more extensive or accessible lexicosemantic network. Furthermore, the N400m peaked at approximately 420 ms and was followed by a large right hemisphere medial occipitoparietal as well as lateral parietal response to concrete words peaking at approximately 550 ms, perhaps embodying imagistic processing. These data suggest that words may be initially understood using a left-lateralized (frontotemporal) verbal-linguistic system that for concrete words is supplemented after a short delay by a right parietal and medial occipital imagistic network.

Adolescent↗

PubMed2006

Laminar population analysis: estimating firing rates and evoked synaptic activity from multielectrode recordings in rat barrel cortex.

We present a new method, laminar population analysis (LPA), for analysis of laminar-electrode (linear multielectrode) data, where physiological constraints are explicitly incorporated in the mathematical model: the high-frequency band [multiunit activity (MUA)] is modeled as a sum over contributions from firing activity of multiple cortical populations, whereas the low-frequency band [local field potential (LFP)] is assumed to reflect the dendritic currents caused by synaptic inputs evoked by this firing. The method is applied to stimulus-averaged laminar-electrode data from barrel cortex of anesthetized rat after single whisker flicks. Two sample data sets, distinguished by stimulus paradigm, type of applied anesthesia, and electrical boundary conditions, are studied in detail. These data sets are well accounted for by a model with four cortical populations: one supragranular, one granular, and two infragranular populations. Population current source densities (CSDs; the CSD signatures after firing in a particular population) provided by LPA are further used to estimate the synaptic connection pattern between the various populations using a new LFP template-fitting technique, where LFP population templates are found by the electrostatic forward solution based on results from compartmental modeling of morphologically reconstructed neurons. Our analysis confirms previous experimental findings regarding the synaptic connections from neurons in the granular layer onto neurons in the supragranular layers and provides predictions about other synaptic connections. Furthermore, the time dependence of the stimulus-evoked population firing activity is predicted, and the temporal ordering of response onset is found to be compatible with earlier findings.

Action Potentials↗

PubMed2006

Frontal connections and cognitive changes in normal aging rhesus monkeys: a DTI study.

Recent anatomical studies have found that cortical neurons are mainly preserved during the aging process while myelin damage and even axonal loss is prominent throughout the forebrain. We used diffusion tensor imaging (DT-MRI) to evaluate the hypothesis that during the process of normal aging, white matter changes preferentially affect the integrity of long corticocortical association fiber tracts, specifically the superior longitudinal fasciculus II and the cingulum bundle. This would disrupt communication between the frontal lobes and other forebrain regions leading to cognitive impairments. We analyzed DT-MRI datasets from seven young and seven elderly behaviorally characterized rhesus monkeys, creating fractional anisotropy (FA) maps of the brain. Significant age-related reductions in mean FA values were found for the superior longitudinal fasciculus II and the cingulum bundle, as well as the anterior corpus callosum. Comparison of these FA reductions with behavioral measures demonstrated a statistically significant linear relationship between regional FA and performance on a test of executive function. These findings support the hypothesis that alterations to the integrity of these long association pathways connecting the frontal lobe with other forebrain regions contribute to cognitive impairments in normal aging. To our knowledge this is the first investigation reporting such alterations in the aging monkey.

Aging↗

PubMed2006

Changes in white matter diffusion anisotropy in adolescents born prematurely.

Being born with very low birth weight (VLBW, birth weight<or=1500 g) or small for gestational age (SGA) carries an increased risk of cerebral white matter damage. The reduced cognitive and motor skills these two groups exhibit suggest that the early injuries to white matter persist into adolescence. White matter integrity was assessed using voxel-wise statistical analysis of fractional anisotropy (FA) maps between three groups of adolescents at age 15; the VLBW group (n=34), the SGA group (n=42) and a control group with normal birth weight (n=47). The FA maps were normalized to a study specific template and group differences were assessed using an analysis of covariance with gender as a confounder (FDR-corrected P<0.05). The main finding is that the VLBW group has significantly reduced FA values in several white matter regions, including the corpus callosum, internal capsule and superior fasciculus compared to the control group. Some of the observed reduction in anisotropy, particularly that observed in the corpus callosum, may have been caused by inaccurate spatial normalization, but this can only explain 30% of the area with reduced anisotropy. Analysis of the eigenvalues of the diffusion tensor show that the reduced FA values in the VLBW group is primarily due to an increase in the two lowest eigenvalues of the diffusion tensor. We speculate that this may be caused by reduced myelination. For the SGA group, we find no statistically significant differences in anisotropy compared to the control group.

Adolescent↗

PubMed2006

The functional and structural significance of the frontal shift in the old/new ERP effect.

There is a lack of studies mapping electrophysiological event-related potentials (ERPs) to structural neuroanatomical characteristics. The aim of the present study was to integrate electrophysiological memory-related activity with cortical and hippocampal volume, as well as psychometric memory performance, in a life-span sample. More specifically, we wanted to investigate the functional significance of the often-observed frontal shift of ERP amplitude with increasing age and whether neuroanatomical characteristics can explain this shift. Sixty six healthy participants (20-78 years) went through a neuropsychological examination, MRI scans, and a visual recognition ERP task with verbal stimuli. The results showed that ERPs elicited in the recognition memory task (the old/new effect) correlated significantly with cortical volume, but not with hippocampal volume. Large cortex predicted more differentiated ERP activity and not just larger amplitude in general, implying more distinct and efficient retrieval. Furthermore, ERP amplitude, cortical volume, and hippocampal volume all predicted scores on a composite memory scale. All these relationship were dependent upon the common influence of age. Finally, the participants with the most anterior distribution of activity showed the poorest recognition memory performance. Neither cortical nor hippocampal volume were related to this frontal shift. It is concluded that the distribution of activity along the anterior-posterior axis in a memory paradigm may have functional but not neuroanatomical volumetric correlates. The functional correlates need not be restricted to the older age groups.

Adult↗

PubMed2006

Regional cortical thickness matters in recall after months more than minutes.

The aim of this study was to determine the role of regional cortical thickness in recall of verbal material over an extended time period. MRI scans of healthy adults of varying ages were obtained. Two scans were averaged per person to achieve high spatial resolution, and a semi-automated method for continuous measurement of thickness across the entire cortical mantle was employed. Verbal memory tests assessing recall after 5 min, 30 min, and a mean interval of 83 days were administered. A general linear model (GLM) of the effects of thickness at each vertex on the different memory indices was computed, controlling for gender, age, IQ, and intracranial volume. These analyses were repeated with hippocampal volume as an additional variable to be controlled for, to assess to which extent effects of cortical thickness were independent of hippocampal size. Minute effects of cortical thickness were observed with regard to shorter time intervals (5 and 30 min). However, even when controlling for the effects of hippocampal volume, higher recall across months was associated with thicker cortex of distinct areas including parts of the gyrus rectus, the middle frontal gyrus, the parieto-occipital sulcus and the lingual gyrus of both hemispheres. In addition, hemisphere-specific associations were found in parts of the right temporal and parietal lobe as well as parts of the left precuneus. This supports a unique and critical role of the thickness of distinct cortical areas in recall after months, more than after minutes.

Adult↗

PubMed2006

Vector-based spatial-temporal minimum L1-norm solution for MEG.

Minimum L1-norm solutions have been used by many investigators to analyze MEG responses because they provide high spatial resolution images. However, conventional minimum L1-norm approaches suffer from instability in spatial construction, and poor smoothness of the reconstructed source time-courses. Activity commonly "jumps" from one grid point to (usually) the neighboring grid points. Equivalently, the time-course of one specific grid point can show substantial "spiky-looking" discontinuity. In the present study, we present a new vector-based spatial-temporal analysis using a L1-minimum-norm (VESTAL). This approach is based on a principle of MEG physics: the magnetic waveforms in sensor-space are linear functions of the source time-courses in the imaging-space. Our computer simulations showed that VESTAL provides good reconstruction of the source amplitude and orientation, with high stability and resolution in both the spatial and temporal domains. "Spiky-looking" discontinuity was not observed in the source time-courses. Importantly, the simulations also showed that VESTAL can resolve sources that are 100% correlated. We then examined the performance of VESTAL in the analysis of human median-nerve MEG responses. The results demonstrated that this method easily distinguishes sources very spatially close to each other, including individual primary somatosensory areas (BA 1, 2, 3b), primary motor area (BA 4), and other regions in the somatosensory system (e.g., BA 5, 7, SII, SMA, and temporal-parietal junction) with high temporal stability and resolution. VESTAL's potential for obtaining information on source extent was also examined.

Adult↗

PubMed2006

An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.

In this study, we have assessed the validity and reliability of an automated labeling system that we have developed for subdividing the human cerebral cortex on magnetic resonance images into gyral based regions of interest (ROIs). Using a dataset of 40 MRI scans we manually identified 34 cortical ROIs in each of the individual hemispheres. This information was then encoded in the form of an atlas that was utilized to automatically label ROIs. To examine the validity, as well as the intra- and inter-rater reliability of the automated system, we used both intraclass correlation coefficients (ICC), and a new method known as mean distance maps, to assess the degree of mismatch between the manual and the automated sets of ROIs. When compared with the manual ROIs, the automated ROIs were highly accurate, with an average ICC of 0.835 across all of the ROIs, and a mean distance error of less than 1 mm. Intra- and inter-rater comparisons yielded little to no difference between the sets of ROIs. These findings suggest that the automated method we have developed for subdividing the human cerebral cortex into standard gyral-based neuroanatomical regions is both anatomically valid and reliable. This method may be useful for both morphometric and functional studies of the cerebral cortex as well as for clinical investigations aimed at tracking the evolution of disease-induced changes over time, including clinical trials in which MRI-based measures are used to examine response to treatment.

Adult↗