Heterogeneity of functional activation during memory encoding across hippocampal subfields in temporal lobe epilepsy

Das, Sandhitsu R.; Mechanic‐Hamilton, Dawn; Pluta, John; Korczykowski, Marc; Detre, John A.; Yushkevich, Paul A.

doi:10.1016/j.neuroimage.2011.06.085

Cited by 21 publications

(16 citation statements)

References 58 publications

(115 reference statements)

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“…While this resulted in complete and accurate subfield identification, clearly in studies with large numbers of participants, this would not be practical. It is therefore essential that the development of automated subfield segmentation continue to be pursued, but this must include the whole hippocampus (not just the body), all major subfields being delineated separately, and basing the segmentations on well-established and agreed anatomy of the hippocampal subfields (e.g., West and Gundersen, 1990; Duvernoy, 2005; Yushkevich et al, 2009). …”

Section: Discussionmentioning

confidence: 99%

“…Segmentation was performed primarily using the Duvernoy (2005) hippocampus atlas as a guide, with West and Gundersen (1990) and Mai et al (2008) as additional resources. Because these guides describe segmentation with 3 mm thick slices, and our slices were 0.5 mm thick, post-mortem data described by Yushkevich et al (2009) acquired at 9.4T and using slices of ~0.2 mm were used as an additional reference.…”

Section: Methodsmentioning

confidence: 99%

“…Intra-rater and inter-rater reliabilities were calculated using the Dice overlap metric (Dice, 1945), defined as the volume of overlap between two ROIs, divided by the mean volume. As in other subfield segmentation studies (Van Leemput et al, 2008; Yushkevich et al, 2009; Malykhin et al, 2010), five consecutive slices located in the body of the hippocampus were chosen. Intra-rater reliability was assessed by comparing two sets of segmentations by HMB with a 6 months interval between segmentations.…”

Section: Methodsmentioning

confidence: 99%

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Multi-voxel pattern analysis in human hippocampal subfields

Bonnici¹,

Chadwick²,

Kumaran³

et al. 2012

Front. Hum. Neurosci.

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A complete understanding of the hippocampus depends on elucidating the representations and computations that exist in its anatomically distinct subfields. High-resolution structural and functional MRI scanning is starting to permit insights into hippocampal subfields in humans. In parallel, such scanning has facilitated the use of multi-voxel pattern analysis (MVPA) to examine information present in the distributed pattern of activity across voxels. The aim of this study was to combine these two relatively new innovations and deploy MVPA in the hippocampal subfields. Delineating subregions of the human hippocampus, a prerequisite for our study, remains a significant challenge, with extant methods often only examining part of the hippocampus, or being unable to differentiate CA3 and dentate gyrus (DG). We therefore devised a new high-resolution anatomical scanning and subfield segmentation protocol that allowed us to overcome these issues, and separately identify CA1, CA3, DG, and subiculum (SUB) across the whole hippocampus using a standard 3T MRI scanner. We then used MVPA to examine fMRI data associated with a decision-making paradigm involving highly similar scenes that had relevance for the computations that occur in hippocampal subfields. Intra- and inter-rater scores for subfield identification using our procedure confirmed its reliability. Moreover, we found that decoding of information within hippocampal subfields was possible using MVPA, with findings that included differential effects for CA3 and DG. We suggest that MVPA in human hippocampal subfields may open up new opportunities to examine how different types of information are represented and processed at this fundamental level.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Multi-voxel pattern analysis in human hippocampal subfields

Bonnici¹,

Chadwick²,

Kumaran³

et al. 2012

Front. Hum. Neurosci.

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“…Unlike the present work, subfields in Yushkevich et al (2009) were labeled in MRI space based on macroscopic features. Using shape-based normalization to in vivo images, the atlas was applied to a study of subfield-specific atrophy in TLE (Das et al, 2011). …”

Section: Prior Workmentioning

confidence: 99%

Histology-derived volumetric annotation of the human hippocampal subfields in postmortem MRI

et al. 2014

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Recently, there has been a growing effort to analyze the morphometry of hippocampal subfields using both in vivo and postmortem magnetic resonance imaging (MRI). However, given that boundaries between subregions of the hippocampal formation (HF) are conventionally defined on the basis of microscopic features that often lack discernible signature in MRI, subfield delineation in MRI literature has largely relied on heuristic geometric rules, the validity of which with respect to the underlying anatomy is largely unknown. The development and evaluation of such rules is challenged by the limited availability of data linking MRI appearance to microscopic hippocampal anatomy, particularly in three dimensions (3D). The present paper, for the first time, demonstrates the feasibility of labeling hippocampal subfields in a high resolution volumetric MRI dataset based directly on microscopic features extracted from histology. It uses a combination of computational techniques and manual post-processing to map subfield boundaries from a stack of histology images (obtained with 200 μm spacing and 5 μm slice thickness; stained using the Kluver-Barrera method) onto a postmortem 9.4 Tesla MRI scan of the intact, whole hippocampal formation acquired with 160 μm isotropic resolution. The histology reconstruction procedure consists of sequential application of a graph-theoretic slice stacking algorithm that mitigates the effects of distorted slices, followed by iterative affine and diffeomorphic co-registration to postmortem MRI scans of approximately 1 cm-thick tissue sub-blocks acquired with 200 μm isotropic resolution. These 1 cm blocks are subsequently co-registered to the MRI of the whole HF. Reconstruction accuracy is evaluated as the average displacement error between boundaries manually delineated in both the histology and MRI following the sequential stages of reconstruction. The methods presented and evaluated in this single-subject study can potentially be applied to multiple hippocampal tissue samples in order to construct a histologically informed MRI atlas of the hippocampal formation.

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“…Recent neuroimaging studies (Das et al, 2011;Suthana et al, 2011;Travis et al, 2014;Yassa et al, 2011) suggest that the DG and CA1-3 may be particularly important for visuo-spatial memory processes including those involved in pattern separation. Studies have linked those subfields to memory performance in healthy younger (Travis et al, 2014) and older adults (Mueller et al, 2012).…”

Section: Introductionmentioning

confidence: 99%