scholarly journals Rapid processing and quantitative evaluation of structural brain scans for adaptive multimodal imaging

2021 ◽  
Author(s):  
František Váša ◽  
Harriet Hobday ◽  
Ryan A. Stanyard ◽  
Richard E. Daws ◽  
Vincent Giampietro ◽  
...  
Keyword(s):  
Quantitative Evaluation ◽  
Multimodal Imaging ◽  
Brain Scans ◽  
Rapid Processing ◽  
Structural Brain

scholarly journals Loneliness is linked to specific subregional alterations in hippocampus-default network co-variation

2021 ◽  
Author(s):  
Chris Zajner ◽  
R. Nathan Spreng ◽  
Danilo Bzdok
Keyword(s):  
Social Deprivation ◽  
Molecular Layer ◽  
Population Level ◽  
Social Neuroscience ◽  
Association Cortex ◽  
Default Network ◽  
White Matter Tract ◽  
Uk Biobank ◽  
Brain Scans ◽  
Structural Brain

Social interaction complexity makes humans unique. But in times of social deprivation this strength risks to expose important vulnerabilities. Human social neuroscience studies have placed a premium on the default network (DN). In contrast, hippocampus (HC) subfields have been intensely studied in rodents and monkeys. To bridge these two literatures, we here quantified how DN subregions systematically co-vary with specific HC subfields in the context of subjective social isolation (i.e., loneliness). By co-decomposition using structural brain scans of ~40,000 UK Biobank participants, loneliness was specially linked to midline subregions in the uncovered DN patterns. These association cortex signatures coincided with concomitant HC patterns implicating especially CA1 and molecular layer. These patterns also showed a strong affiliation with the fornix white-matter tract and the nucleus accumbens. In addition, separable signatures of structural HC-DN co-variation had distinct associations with the genetic predisposition for loneliness at the population level.

scholarly journals Brain scans from 21297 individuals reveal the genetic architecture of hippocampal subfield volumes

2018 ◽  
Author(s):  
Dennis van der Meer ◽  
Jaroslav Rokicki ◽  
Tobias Kaufmann ◽  
Aldo Córdova-Palomera ◽  
Torgeir Moberget ◽  
...  
Keyword(s):  
Genetic Architecture ◽  
Genetic Correlations ◽  
Hippocampal Volume ◽  
Heterogeneous Structure ◽  
Intracranial Volume ◽  
Brain Scans ◽  
Hippocampal Subfields ◽  
Genome Wide ◽  
A Genome ◽  
Structural Brain

ABSTRACTThe hippocampus is a heterogeneous structure, comprising histologically distinguishable subfields. These subfields are differentially involved in memory consolidation, spatial navigation and pattern separation, complex functions often impaired in individuals with brain disorders characterized by reduced hippocampal volume, including Alzheimer’s disease (AD) and schizophrenia. Given the structural and functional heterogeneity of the hippocampal formation, we sought to characterize the subfields’ genetic architecture. T1-weighted brain scans (n=21297, 16 cohorts) were processed with the hippocampal subfields algorithm in FreeSurfer v6.0. We ran a genome-wide association analysis on each subfield, covarying for total hippocampal volume. We further calculated the single nucleotide polymorphism (SNP)-based heritability of twelve subfields, as well as their genetic correlation with each other, with other structural brain features, and with AD and schizophrenia. All outcome measures were corrected for age, sex, and intracranial volume. We found 15 unique genome-wide significant loci across six subfields, of which eight had not been previously linked to the hippocampus. Top SNPs were mapped to genes associated with neuronal differentiation, locomotor behaviour, schizophrenia and AD. The volumes of all the subfields were estimated to be heritable (h2 from .14 to .27, all p< 1×10-16) and clustered together based on their genetic correlations compared to other structural brain features. There was also evidence of genetic overlap of subicular subfield volumes with schizophrenia. We conclude that hippocampal subfields have partly distinct genetic determinants associated with specific biological processes and traits. Taking into account this specificity may increase our understanding of hippocampal neurobiology and associated pathologies.

scholarly journals Subjective social isolation is linked to subregional alterations in hippocampus-default network co-variation

2021 ◽  
Author(s):  
Chris Zajner ◽  
Robert Nathan Spreng ◽  
Danilo Bzdok
Keyword(s):  
Social Isolation ◽  
Social Deprivation ◽  
Molecular Layer ◽  
Population Level ◽  
Social Neuroscience ◽  
Association Cortex ◽  
Default Network ◽  
Uk Biobank ◽  
Brain Scans ◽  
Structural Brain

Social interaction complexity makes humans unique. But in times of social deprivation this strength risks to expose important vulnerabilities. Human social neuroscience studies have placed a premium on the default network (DN). In contrast, hippocampus (HC) subfields have been intensely studied in rodents and monkeys. To bridge these two literatures, we here quantified how DN subregions systematically co-vary with specific HC subfields in the context of subjective social isolation (i.e., loneliness). By co-decomposition using structural brain scans of ~40,000 UK Biobank participants, loneliness was specially linked to midline subregions in the uncovered DN patterns. These association cortex signatures coincided with concomitant HC patterns implicating especially CA1 and molecular layer. These patterns also showed a strong affiliation with the fornix white-matter tract and the nucleus accumbens. In addition, separable signatures of structural HC-DN co-variation had distinct associations with the genetic predisposition for loneliness at the population level.

scholarly journals Multicenter Voxel-Based Morphometry Mega-Analysis of Structural Brain Scans in Obsessive-Compulsive Disorder

2015 ◽  
Vol 13 (2) ◽  
pp. 204-212
Author(s):  
Stella J. de Wit ◽  
Pino Alonso ◽  
Lizanne Schweren ◽  
David Mataix-Cols ◽  
Christine Lochner ◽  
...  
Keyword(s):  
Obsessive Compulsive Disorder ◽  
Voxel Based Morphometry ◽  
Obsessive Compulsive ◽  
Brain Scans ◽  
Compulsive Disorder ◽  
Structural Brain

scholarly journals Multicenter Voxel-Based Morphometry Mega-Analysis of Structural Brain Scans in Obsessive-Compulsive Disorder

2014 ◽  
Vol 171 (3) ◽  
pp. 340-349 ◽  
Author(s):  
Stella J. de Wit ◽  
Pino Alonso ◽  
Lizanne Schweren ◽  
David Mataix-Cols ◽  
Christine Lochner ◽  
...  
Keyword(s):  
Obsessive Compulsive Disorder ◽  
Voxel Based Morphometry ◽  
Obsessive Compulsive ◽  
Brain Scans ◽  
Compulsive Disorder ◽  
Structural Brain

scholarly journals Brain scans from 21,297 individuals reveal the genetic architecture of hippocampal subfield volumes

2018 ◽  
Vol 25 (11) ◽  
pp. 3053-3065 ◽  
Author(s):  
Dennis van der Meer ◽  
◽  
Jaroslav Rokicki ◽  
Tobias Kaufmann ◽  
Aldo Córdova-Palomera ◽  
...  
Keyword(s):  
Genetic Architecture ◽  
Genetic Correlations ◽  
Hippocampal Volume ◽  
Heterogeneous Structure ◽  
Intracranial Volume ◽  
Brain Scans ◽  
Hippocampal Subfields ◽  
Genome Wide ◽  
A Genome ◽  
Structural Brain

Abstract The hippocampus is a heterogeneous structure, comprising histologically distinguishable subfields. These subfields are differentially involved in memory consolidation, spatial navigation and pattern separation, complex functions often impaired in individuals with brain disorders characterized by reduced hippocampal volume, including Alzheimer’s disease (AD) and schizophrenia. Given the structural and functional heterogeneity of the hippocampal formation, we sought to characterize the subfields’ genetic architecture. T1-weighted brain scans (n = 21,297, 16 cohorts) were processed with the hippocampal subfields algorithm in FreeSurfer v6.0. We ran a genome-wide association analysis on each subfield, co-varying for whole hippocampal volume. We further calculated the single-nucleotide polymorphism (SNP)-based heritability of 12 subfields, as well as their genetic correlation with each other, with other structural brain features and with AD and schizophrenia. All outcome measures were corrected for age, sex and intracranial volume. We found 15 unique genome-wide significant loci across six subfields, of which eight had not been previously linked to the hippocampus. Top SNPs were mapped to genes associated with neuronal differentiation, locomotor behaviour, schizophrenia and AD. The volumes of all the subfields were estimated to be heritable (h2 from 0.14 to 0.27, all p < 1 × 10–16) and clustered together based on their genetic correlations compared with other structural brain features. There was also evidence of genetic overlap of subicular subfield volumes with schizophrenia. We conclude that hippocampal subfields have partly distinct genetic determinants associated with specific biological processes and traits. Taking into account this specificity may increase our understanding of hippocampal neurobiology and associated pathologies.

scholarly journals Brain morphology and neurological soft signs in adolescents with first-episode psychosis

2009 ◽  
Vol 195 (3) ◽  
pp. 227-233 ◽  
Author(s):  
Joost Janssen ◽  
Angeles Diaz-Caneja ◽  
Santiago Reig ◽  
Igor Bombín ◽  
María Mayoral ◽  
...  
Keyword(s):  
First Episode Psychosis ◽  
Brain Morphology ◽  
First Episode ◽  
Neurological Soft Signs ◽  
Brain Volumes ◽  
Brain Scans ◽  
Episode Psychosis ◽  
Complex Motor ◽  
Left Thalamus ◽  
Structural Brain

BackgroundAdolescents with first-episode psychosis have increased severity of neurological soft signs when compared with controls, but it is unclear whether increased severity of neurological soft signs is an expression of specific structural brain deficits.AimsTo examine whether increased severity of neurological soft signs was associated with decreased brain volumes in adolescents with first-episode psychosis.MethodBrain scans were obtained for 70 adolescents (less than 18 years of age) with first-episode psychosis (duration of positive symptoms less than 6 months). Volumes were assessed using voxel-based morphometry and through segmentation of anatomical structures.ResultsIncreased severity of sensory integration neurological soft signs correlated with smaller right and left thalamus volume, whereas increased severity of sequencing of complex motor acts neurological soft signs correlated with smaller right caudate volume.ConclusionsNeurological soft signs may be an easy-to-assess marker of region-specific structural brain deficits in adolescents with first-episode psychosis.

scholarly journals Rapid processing and quantitative evaluation of multicontrast EPImix scans for adaptive multimodal imaging

2021 ◽  
Author(s):  
František Váša ◽  
Harriet Hobday ◽  
Ryan A. Stanyard ◽  
Richard E. Daws ◽  
Vincent Giampietro ◽  
...  
Keyword(s):  
Multimodal Imaging ◽  
Quantitative Information ◽  
Rapid Acquisition ◽  
Rapid Construction ◽  
Neuroimaging Data ◽  
Mri Scans ◽  
Rapid Processing ◽  
The Impact ◽  
Derived Data

AbstractCurrent neuroimaging acquisition and processing approaches tend to be optimised for quality rather than speed. However, rapid acquisition and processing of neuroimaging data can lead to novel neuroimaging paradigms, such as adaptive acquisition, where rapidly processed data is used to inform subsequent image acquisition steps. Here we first evaluate the impact of several processing steps on the processing time and quality of registration of manually labelled T1-weighted MRI scans. Subsequently, we apply the selected rapid processing pipeline both to rapidly acquired multicontrast EPImix scans of 95 participants (which include T1-FLAIR, T2, T2*, T2-FLAIR, DWI & ADC contrasts, acquired in ∼1 minute), as well as to slower, more standard single-contrast T1-weighted scans of a subset of 66 participants. We quantify the correspondence between EPImix and single-contrast T1-weighted scans, using correlations between voxels and regions of interest across participants, measures of within- and between-participant identifiability as well as regional structural covariance networks. Furthermore, we explore the use of EPImix for the rapid construction of morphometric similarity networks. Finally, we quantify the reliability of EPImix-derived data using test-retest scans of 10 participants. Our results demonstrate that quantitative information can be derived from a neuroimaging scan acquired and processed within minutes, which could further be used to implement adaptive multimodal imaging and tailor neuroimaging examinations to individual patients.Abstract FigureGraphical abstract.

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