The Perirhinal, Entorhinal, and Parahippocampal Cortices and Hippocampus: An Overview of Functional Anatomy and Protocol for Their Segmentation in MR Images

Kivisaari, Sasa L.; Probst, A.; Taylor, Kirsten I.

doi:10.1007/978-3-642-34342-1_19

Cited by 38 publications

(51 citation statements)

References 183 publications

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“…We verified our results in a left perirhinal VOI that was defined based on anatomical landmarks (Insausti et al, 1998;Kivisaari et al, 2013). We manually delineated the left perirhinal cortex on the single subject T1 template of SPM8 based on the anatomical landmarks following the guidelines of Insausti et al (1998) and Kivisaari et al (2013).…”

Section: Definition Of the Left Perirhinal Voisupporting

confidence: 57%

“…Its mathematical centre is at x = -26 , y = -25, and z = -14, its most anterior border at y = -15 mm and its most posterior border at y = -35 mm. The VOI contains the posterior half of perirhinal cortex but also an anterior portion of the parahippocampal gyrus and extends medially into the transentorhinal and entorhinal cortex and hippocampal body (Insausti et al, 1998;Kivisaari et al, 2013) (Fig. 3A).…”

Section: Definition Of the Left Perirhinal Voimentioning

confidence: 99%

“…We manually delineated the left perirhinal cortex on the single subject T1 template of SPM8 based on the anatomical landmarks following the guidelines of Insausti et al (1998) and Kivisaari et al (2013). From this VOI we excluded voxels that fell outside the mask obtained in the univariate SPM analysis in any of the subjects.…”

Section: Definition Of the Left Perirhinal Voimentioning

confidence: 99%

“…The VOI imported from Bruffaerts et al (2013b) contained the posterior half of perirhinal cortex, and also extended into the rostral portion of the parahippocampal gyrus and medially into entorhinal cortex and the hippocampus (Insausti et al, 1998;Kivisaari et al, 2013) (Fig. 3).…”

Section: Alternative Explanations and Limitationsmentioning

confidence: 99%

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Left perirhinal cortex codes for similarity in meaning between written words: Comparison with auditory word input

et al. 2015

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This is a pre-copy-editing, author-produced PDF of an article accepted for publication in Neuropsychologia following peer review. The definitive publisher-authenticated version (Liuzzi A.G., Bruffaerts R., Dupont P., Adamczuk K., Peeters R., De Deyne S., Storms G., Vandenberghe R. AbstractLeft perirhinal cortex has been previously implicated in associative coding. According to a recent experiment, the similarity of perirhinal fMRI response patterns to written concrete words is higher for words which are more similar in their meaning. If left perirhinal cortex functions as an amodal semantic hub, one would predict that this semantic similarity effect would extend to the spoken modality. We conducted an event-related fMRI experiment and evaluated whether a same semantic similarity effect could be obtained for spoken as for written words. Twenty healthy subjects performed a property verification task in either the written or the spoken modality. Words corresponded to concrete animate entities for which extensive feature generation was available from more than 1000 subjects. From these feature generation data, a concept-feature matrix was derived which formed the basis of a cosine similarity matrix between the entities reflecting their similarity in meaning (called the "semantic cossimilarity matrix"). Independently, we calculated a cosine similarity matrix between the left perirhinal fMRI activity patterns evoked by the words (called the "fMRI cossimilarity matrix"). Next, the similarity was determined between the semantic cossimilarity matrix and the fMRI cossimilarity matrix. This was done for written and spoken words pooled, for written words only, for spoken words only, as well as for crossmodal pairs. Only for written words did the fMRI cossimilarity matrix correlate with the semantic cossimilarity matrix. Contrary to our prediction, we did not find any such effect for auditory word input nor did we find cross-modal effects in perirhinal cortex between written and auditory words. Our findings situate the contribution of left perirhinal cortex to word processing at the top of the visual processing pathway, rather than at an amodal stage where visual and auditory word processing pathways have already converged.

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Section: Definition Of the Left Perirhinal Voisupporting

confidence: 57%

Section: Definition Of the Left Perirhinal Voimentioning

confidence: 99%

Section: Definition Of the Left Perirhinal Voimentioning

confidence: 99%

Section: Alternative Explanations and Limitationsmentioning

confidence: 99%

See 2 more Smart Citations

Left perirhinal cortex codes for similarity in meaning between written words: Comparison with auditory word input

et al. 2015

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“…MPRAGEs were preprocessed in FreeSurfer (http:/surfer.nmr.mgh.harvard.edu) as described elsewhere [14] and regions of interest (ROIs) for the mPRC and ERC were drawn by the same, blinded rater on cortical surface reconstructions of segmented T1-weighted images based on anatomical landmarks described elsewhere [23,24]. Only left hemisphere ROIs were drawn because of the verbal nature of the neuropsychological tasks.…”

Section: Mrimentioning

confidence: 99%

Neuropsychological Markers of Medial Perirhinal and Entorhinal Cortex Functioning are Impaired Twelve Years Preceding Diagnosis of Alzheimer’s Dementia

Hirni

Kivisaari

Krumm

et al. 2016

JAD

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Abstract. Neurofibrillary pathology in Alzheimer's dementia (AD) is associated with cognitive impairments and cortical thinning, and begins in medial perirhinal cortex (mPRC) before entering entorhinal cortex (ERC). Thus, mPRC dysfunction (e.g., semantic object memory impairments) may predate or accompany ERC (i.e., episodic memory) dysfunction in the preclinical course of typical AD. We developed formulae estimating mPRC and ERC integrity (i.e., cortical thickness) using common neuropsychological tests in 31 healthy individuals and 58 early AD patients. These formulae estimated the longitudinal courses of mPRC and ERC functioning in independent groups of 28 optimally healthy individuals who developed AD (NC-AD) over 2.8-13.4 years and 28 pairwise-matched, stable, healthy individuals (NC-NC). Mixed models demonstrated significantly worse NC-AD than NC-NC estimated mPRC and ERC functioning at the earliest observation,

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Automated segmentation of medial temporal lobe subregions on in vivo T1‐weighted MRI in early stages of Alzheimer's disease

Xie

Wisse

Pluta

et al. 2019

Human Brain Mapping

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Medial temporal lobe (MTL) substructures are the earliest regions affected by neurofibrillary tangle pathology—and thus are promising biomarkers for Alzheimer’s disease (AD). However, automatic segmentation of the MTL using only T1-weighted (T1w) magnetic resonance imaging (MRI) is challenging due to the large anatomical variability of the MTL cortex and the confound of the dura mater, which is commonly segmented as gray matter by state-of-the-art algorithms because they have similar intensity in T1w MRI. To address these challenges, we developed a novel atlas set, consisting of 15 cognitively normal older adults and 14 patients with mild cognitive impairment with a label explicitly assigned to the dura, that can be used by the multiatlas automated pipeline (Automatic Segmentation of Hippocampal Subfields [ASHS-T1]) for the segmentation of MTL subregions, including anterior/posterior hippocampus, entorhinal cortex (ERC), Brodmann areas (BA) 35 and 36, and parahippocampal cortex on T1w MRI. Cross-validation experiments indicated good segmentation accuracy of ASHS-T1 and that the dura can be reliably separated from the cortex (6.5% mislabeled as gray matter). Conversely, FreeSurfer segmented majority of the dura mater (62.4%) as gray matter and the degree of dura mislabeling decreased with increasing disease severity. To evaluate its clinical utility, we applied the pipeline to T1w images of 663 ADNI subjects and significant volume/thickness loss is observed in BA35, ERC, and posterior hippocampus in early prodromal AD and all subregions at later stages. As such, the publicly available new atlas and ASHS-T1 could have important utility in the early diagnosis and monitoring of AD and enhancing brain-behavior studies of these regions.

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The Perirhinal, Entorhinal, and Parahippocampal Cortices and Hippocampus: An Overview of Functional Anatomy and Protocol for Their Segmentation in MR Images

Cited by 38 publications

References 183 publications

Left perirhinal cortex codes for similarity in meaning between written words: Comparison with auditory word input

Left perirhinal cortex codes for similarity in meaning between written words: Comparison with auditory word input

Neuropsychological Markers of Medial Perirhinal and Entorhinal Cortex Functioning are Impaired Twelve Years Preceding Diagnosis of Alzheimer’s Dementia

Automated segmentation of medial temporal lobe subregions on in vivo T1‐weighted MRI in early stages of Alzheimer's disease

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