Hippocampal subregion abnormalities in schizophrenia: A systematic review of structural and physiological imaging studies.

AimThe hippocampus is considered a key region in schizophrenia pathophysiology, but the nature of hippocampal subregion abnormalities and how they contribute to disease expression remain to be fully determined. This study reviews findings from schizophrenia hippocampal subregion volumetric and physiological imaging studies published within the last decade.MethodsThe PubMed database was searched for publications on hippocampal subregion volume and physiology abnormalities in schizophrenia and their findings were reviewed.ResultsThe main replicated findings include smaller CA1 volumes and CA1 hyperactivation in schizophrenia, which may be predictive of conversion in individuals at clinical high risk of psychosis, smaller CA1 and CA4/DG volumes in first-episode schizophrenia, and more widespread smaller hippocampal subregion volumes with longer duration of illness. Several studies have reported relationships between hippocampal subregion volumes and declarative memory or symptom severity.ConclusionsTogether these studies provide support for hippocampal formation circuitry models of schizophrenia. These initial findings must be taken with caution as the scientific community is actively working on hippocampal subregion method improvement and validation. Further improvements in our understanding of the nature of hippocampal formation subregion involvement in schizophrenia will require the collection of structural and physiological imaging data at submillimeter voxel resolution, standardization and agreement of atlases, adequate control for possible confounding factors, and multi-method validation of findings. Despite the need for cautionary interpretation of the initial findings, we believe that improved localization of hippocampal subregion abnormalities in schizophrenia holds promise for the identification of disease contributing mechanisms

Hippocampal subfields at ultra high field MRI: An overview of segmentation and measurement methods

The hippocampus is one of the most interesting and studied brain regions because of its involvement in memory functions and its vulnerability in pathological conditions, such as neurodegenerative processes. In the recent years, the increasing availability of Magnetic Resonance Imaging (MRI) scanners that operate at ultra-high field (UHF), that is, with static magnetic field strength ≥7T, has opened new research perspectives. Compared to conventional high-field scanners, these systems can provide new contrasts, increased signal-to-noise ratio and higher spatial resolution, thus they may improve the visualization of very small structures of the brain, such as the hippocampal subfields. Studying the morphometry of the hippocampus is crucial in neuroimaging research because changes in volume and thickness of hippocampal subregions may be relevant in the early assessment of pathological cognitive decline and Alzheimer's Disease (AD). The present review provides an overview of the manual, semi-automated and fully automated methods that allow the assessment of hippocampal subfield morphometry at UHF MRI, focusing on the different hippocampal segmentation produced. © 2017 Wiley Periodicals, Inc

Brain Differences in the Prefrontal Cortex, Amygdala, and Hippocampus in Youth with Congenital Adrenal Hyperplasia

Context: Classical Congenital Adrenal Hyperplasia (CAH) due to 21-hydroxylase deficiency results in hormone imbalances present both prenatally and postnatally that may impact the developing brain. Objective: To characterize gray matter morphology in the prefrontal cortex and subregion volumes of the amygdala and hippocampus in youth with CAH, compared to controls. Design: A cross-sectional study of 27 CAH youth (16 female; 12.6 ± 3.4 year) and 35 typically developing, healthy controls (20 female; 13.0 ± 2.8 year) with 3-T magnetic resonance imaging scans. Brain volumes of interest included bilateral prefrontal cortex, and nine amygdala and six hippocampal subregions. Between-subject effects of group (CAH vs control) and sex, and their interaction (group-by-sex) on brain volumes were studied, while controlling for intracranial volume (ICV) and group differences in body mass index and bone age. Results: CAH youth had smaller ICV and increased cerebrospinal fluid volume compared to controls. In fully-adjusted models, CAH youth had smaller bilateral, superior and caudal middle frontal volumes, and smaller left lateral orbito-frontal volumes compared to controls. Medial temporal lobe analyses revealed the left hippocampus was smaller in fully-adjusted models. CAH youth also had significantly smaller lateral nucleus of the amygdala and hippocampal subiculum and CA1 subregions. Conclusions: This study replicates previous findings of smaller medial temporal lobe volumes in CAH patients, and suggests that lateral nucleus of the amygdala, as well as subiculum and subfield CA1 of the hippocampus are particularly affected within the medial temporal lobes in CAH youth

Automated Segmentation of Hippocampal Subfields From Ultra-High Resolution In Vivo MRI

Recent developments in MRI data acquisition technology are starting to yield images that show anatomical features of the hippocampal formation at an unprecedented level of detail, providing the basis for hippocampal subfield measurement. However, a fundamental bottleneck in MRI studies of the hippocampus at the subfield level is that they currently depend on manual segmentation, a laborious process that severely limits the amount of data that can be analyzed. In this article, we present a computational method for segmenting the hippocampal subfields in ultra-high resolution MRI data in a fully automated fashion. Using Bayesian inference, we use a statistical model of image formation around the hippocampal area to obtain automated segmentations. We validate the proposed technique by comparing its segmentations to corresponding manual delineations in ultra-high resolution MRI scans of 10 individuals, and show that automated volume measurements of the larger subfields correlate well with manual volume estimates. Unlike manual segmentations, our automated technique is fully reproducible, and fast enough to enable routine analysis of the hippocampal subfields in large imaging studies.National Institutes of Health (U.S.) (NIH NCRR; Grant number: P41-RR14075)National Institutes of Health (U.S.) (Grant R01 RR16594-01A1)National Institutes of Health (U.S.) (Grant NAC P41-RR13218)Biomedical Informatics Research Network (BIRN002)Biomedical Informatics Research Network (U24 RR021382)National Institute of Biomedical Imaging and Bioengineering (U.S.) (R01 EB001550)National Institute of Biomedical Imaging and Bioengineering (U.S.) (R01EB006758)National Institute of Biomedical Imaging and Bioengineering (U.S.) (NAMIC U54-EB005149)National Institute of Neurological Disorders and Stroke (U.S.) (R01 NS052585-01)National Institute of Neurological Disorders and Stroke (U.S.) (R01 NS051826)Mental Illness and Neuroscience Discovery (MIND) InstituteEllison Medical Foundation (Autism & Dyslexia Project

Unravelling The Subfields Of The Hippocampal Head Using 7-Tesla Structural MRI

Probing the functions of human hippocampal subfields is a promising area of research in cognitive neuroscience. However, defining subfield borders in Magnetic Resonance Imaging (MRI) is challenging. Here, we present a user-guided, semi-automated protocol for segmenting hippocampal subfields on T2-weighted images obtained with 7-Tesla MRI. The protocol takes advantage of extant knowledge about regularities in hippocampal morphology and ontogeny that have not been systematically considered in prior related work. An image feature known as the hippocampal ‘dark band’ facilitates tracking of subfield continuities, allowing for unfolding and segmentation of convoluted hippocampal tissue. Initial results suggest that this protocol offers sufficient precision and flexibility to accommodate inter-individual differences in morphology and produces segmentations that have improved accuracy and detail compared to other prominent protocols, with similar inter-rater reliability. We anticipate that this protocol will allow for improved anatomical precision in future research on hippocampal subfields in health and neurological disease

Building a surface atlas of hippocampal subfields from high resolution T2-weighted MRI scans using landmark-free surface registration

The hippocampus is widely studied in neuroimaging field as it plays important roles in memory and learning. However, the critical subfield information is often not explored in most hippocampal studies. We previously proposed a method for hippocampal subfield morphometry by integrating FreeSurfer, FSL, and SPHARM tools. But this method had some limitations, including the analysis of T1-weighted MRI scans without detailed subfield information and hippocampal registration without using important subfield information. To bridge these gaps, in this work, we propose a new framework for building a surface atlas of hippocampal subfields from high resolution T2-weighted MRI scans by integrating state-of-the-art methods for automated segmentation of hippocampal subfields and landmark-free, subfield-aware registration of hippocampal surfaces. Our experimental results have shown the promise of the new framework

Recognition Memory Dysfunction Relates to Hippocampal Subfield Volume: A Study of Cognitively Normal and Mildly Impaired Older Adults.

ObjectivesThe current study examined recognition memory dysfunction and its neuroanatomical substrates in cognitively normal older adults and those diagnosed with mild cognitive impairment (MCI).MethodsParticipants completed the Mnemonic Similarity Task, which provides simultaneous measures of recognition memory and mnemonic discrimination. They also underwent structural neuroimaging to assess volume of medial temporal cortex and hippocampal subfields.ResultsAs expected, individuals diagnosed with MCI had significantly worse recognition memory performance and reduced volume across medial temporal cortex and hippocampal subfields relative to cognitively normal older adults. After controlling for diagnostic group differences, however, recognition memory was significantly related to whole hippocampus volume, and to volume of the dentate gyrus/CA3 subfield in particular. Recognition memory was also related to mnemonic discrimination, a fundamental component of episodic memory that has previously been linked to dentate gyrus/CA3 structure and function.DiscussionResults reveal that hippocampal subfield volume is sensitive to individual differences in recognition memory in older adults independent of clinical diagnosis. This supports the notion that episodic memory declines along a continuum within this age group, not just between diagnostic groups

Ultra-high-field fMRI reveals a role for the subiculum in scene perceptual discrimination

Recent “representational” accounts suggest a key role for the hippocampus in complex scene perception. Due to limitations in scanner field strength, however, the functional neuroanatomy of hippocampal-dependent scene perception is unknown. Here, we applied 7 T high-resolution functional magnetic resonance imaging (fMRI) alongside a perceptual oddity task, modified from nonhuman primate studies. This task requires subjects to discriminate highly similar scenes, faces, or objects from multiple viewpoints, and has revealed selective impairments during scene discrimination following hippocampal lesions. Region-of-interest analyses identified a preferential response in the subiculum subfield of the hippocampus during scene, but not face or object, discriminations. Notably, this effect was in the anteromedial subiculum and was not modulated by whether scenes were subsequently remembered or forgotten. These results highlight the value of ultra-high-field fMRI in generating more refined, anatomically informed, functional accounts of hippocampal contributions to cognition, and a unique role for the human subiculum in discrimination of complex scenes from different viewpoints