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Coman DA, Ionita S, Lita I. Evaluation of EEG Signals by Spectral Peak Methods and Statistical Correlation for Mental State Discrimination Induced by Arithmetic Tasks. SENSORS (BASEL, SWITZERLAND) 2024; 24:3316. [PMID: 38894108 PMCID: PMC11174818 DOI: 10.3390/s24113316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 05/16/2024] [Accepted: 05/20/2024] [Indexed: 06/21/2024]
Abstract
Bringing out brain activity through the interpretation of EEG signals is a challenging problem that involves combined methods of signal analysis. The issue of classifying mental states induced by arithmetic tasks can be solved through various classification methods, using diverse characteristic parameters of EEG signals in the time, frequency, and statistical domains. This paper explores the results of an experiment that aimed to highlight arithmetic mental tasks contained in the PhysioNet database, performed on a group of 36 subjects. The majority of publications on this topic deal with machine learning (ML)-based classification methods with supervised learning support vector machine (SVM) algorithms, K-Nearest Neighbor (KNN), Linear Discriminant Analysis (LDA), and Decision Trees (DTs). Also, there are frequent approaches based on the analysis of EEG data as time series and their classification with Recurrent Neural Networks (RNNs), as well as with improved algorithms such as Long Short-Term Memory (LSTM), Bidirectional Long Short-Term Memory (BLSTM), and Gated Recurrent Units (GRUs). In the present work, we evaluate the classification method based on the comparison of domain limits for two specific characteristics of EEG signals: the statistical correlation of pairs of signals and the size of the spectral peak detected in theta, alpha, and beta bands. This study provides some interpretations regarding the electrical activity of the brain, consolidating and complementing the results of similar research. The classification method used is simple and easy to apply and interpret. The analysis of EEG data showed that the theta and beta frequency bands were the only discriminators between the relaxation and arithmetic calculation states. Notably, the F7 signal, which used the spectral peak criterion, achieved the best classification accuracy (100%) in both theta and beta bands for the subjects with the best results in performing calculations. Also, our study found the Fz signal to be a good sensor in the theta band for mental task discrimination for all subjects in the group with 90% accuracy.
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Affiliation(s)
- Daniela Andreea Coman
- Department of Electronics, Computers and Electrical Engineering, National University of Science and Technology POLITEHNICA Bucharest, 110040 Pitesti, Romania;
- Regional Research and Development Center for Innovative Materials, Processes, and Products for the Automotive Industry (CRC&D-Auto), 110440 Pitesti, Romania
| | - Silviu Ionita
- Department of Electronics, Computers and Electrical Engineering, National University of Science and Technology POLITEHNICA Bucharest, 110040 Pitesti, Romania;
| | - Ioan Lita
- Department of Electronics, Computers and Electrical Engineering, National University of Science and Technology POLITEHNICA Bucharest, 110040 Pitesti, Romania;
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2
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Wuestefeld A, Baumeister H, Adams JN, de Flores R, Hodgetts CJ, Mazloum-Farzaghi N, Olsen RK, Puliyadi V, Tran TT, Bakker A, Canada KL, Dalton MA, Daugherty AM, La Joie R, Wang L, Bedard ML, Buendia E, Chung E, Denning A, Del Mar Arroyo-Jiménez M, Artacho-Pérula E, Irwin DJ, Ittyerah R, Lee EB, Lim S, Del Pilar Marcos-Rabal M, Iñiguez de Onzoño Martin MM, Lopez MM, de la Rosa Prieto C, Schuck T, Trotman W, Vela A, Yushkevich P, Amunts K, Augustinack JC, Ding SL, Insausti R, Kedo O, Berron D, Wisse LEM. Comparison of histological delineations of medial temporal lobe cortices by four independent neuroanatomy laboratories. Hippocampus 2024; 34:241-260. [PMID: 38415962 PMCID: PMC11039382 DOI: 10.1002/hipo.23602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 01/25/2024] [Accepted: 02/04/2024] [Indexed: 02/29/2024]
Abstract
The medial temporal lobe (MTL) cortex, located adjacent to the hippocampus, is crucial for memory and prone to the accumulation of certain neuropathologies such as Alzheimer's disease neurofibrillary tau tangles. The MTL cortex is composed of several subregions which differ in their functional and cytoarchitectonic features. As neuroanatomical schools rely on different cytoarchitectonic definitions of these subregions, it is unclear to what extent their delineations of MTL cortex subregions overlap. Here, we provide an overview of cytoarchitectonic definitions of the entorhinal and parahippocampal cortices as well as Brodmann areas (BA) 35 and 36, as provided by four neuroanatomists from different laboratories, aiming to identify the rationale for overlapping and diverging delineations. Nissl-stained series were acquired from the temporal lobes of three human specimens (two right and one left hemisphere). Slices (50 μm thick) were prepared perpendicular to the long axis of the hippocampus spanning the entire longitudinal extent of the MTL cortex. Four neuroanatomists annotated MTL cortex subregions on digitized slices spaced 5 mm apart (pixel size 0.4 μm at 20× magnification). Parcellations, terminology, and border placement were compared among neuroanatomists. Cytoarchitectonic features of each subregion are described in detail. Qualitative analysis of the annotations showed higher agreement in the definitions of the entorhinal cortex and BA35, while the definitions of BA36 and the parahippocampal cortex exhibited less overlap among neuroanatomists. The degree of overlap of cytoarchitectonic definitions was partially reflected in the neuroanatomists' agreement on the respective delineations. Lower agreement in annotations was observed in transitional zones between structures where seminal cytoarchitectonic features are expressed less saliently. The results highlight that definitions and parcellations of the MTL cortex differ among neuroanatomical schools and thereby increase understanding of why these differences may arise. This work sets a crucial foundation to further advance anatomically-informed neuroimaging research on the human MTL cortex.
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Affiliation(s)
- Anika Wuestefeld
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Hannah Baumeister
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Jenna N Adams
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, California, USA
| | - Robin de Flores
- INSERM UMR-S U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Caen-Normandie University, GIP Cyceron, France
| | | | - Negar Mazloum-Farzaghi
- University of Toronto, Toronto, Ontario, Canada
- Rotman Research Institute, Toronto, Ontario, Canada
| | - Rosanna K Olsen
- University of Toronto, Toronto, Ontario, Canada
- Rotman Research Institute, Toronto, Ontario, Canada
| | - Vyash Puliyadi
- Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, Maryland, USA
| | - Tammy T Tran
- Department of Psychology, Stanford University, Stanford, California, USA
| | - Arnold Bakker
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, Maryland, USA
| | - Kelsey L Canada
- Institute of Gerontology, Wayne State University, Detroit, Michigan, USA
| | | | - Ana M Daugherty
- Institute of Gerontology, Wayne State University, Detroit, Michigan, USA
- Department of Psychology, Wayne State University, Detroit, Michigan, USA
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, California, USA
| | - Lei Wang
- The Ohio State University, Columbus, Ohio, USA
| | - Madigan L Bedard
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Esther Buendia
- Human Neuroanatomy Laboratory, University of Castilla-La Mancha, Albacete, Spain
| | - Eunice Chung
- University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Amanda Denning
- University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | | | | | - David J Irwin
- University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | | | - Edward B Lee
- University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Sydney Lim
- University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | | | | | - Monica Munoz Lopez
- Human Neuroanatomy Laboratory, University of Castilla-La Mancha, Albacete, Spain
| | | | - Theresa Schuck
- University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | | | - Alicia Vela
- Human Neuroanatomy Laboratory, University of Castilla-La Mancha, Albacete, Spain
| | | | - Katrin Amunts
- Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany
- C. & O. Vogt Institute for Brain Research, Medical Faculty, University Hospital Düsseldorf, Heinrich-Heine-University, Düsseldorf, Germany
| | | | - Song-Lin Ding
- Allen Institute for Brain Science, Seattle, Washington, USA
| | - Ricardo Insausti
- Human Neuroanatomy Laboratory, University of Castilla-La Mancha, Albacete, Spain
| | - Olga Kedo
- Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany
| | - David Berron
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Laura E M Wisse
- Department of Diagnostic Radiology, Lund University, Lund, Sweden
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3
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Wuestefeld A, Baumeister H, Adams JN, de Flores R, Hodgetts C, Mazloum-Farzaghi N, Olsen RK, Puliyadi V, Tran TT, Bakker A, Canada KL, Dalton MA, Daugherty AM, Joie RL, Wang L, Bedard M, Buendia E, Chung E, Denning A, Arroyo-Jiménez MDM, Artacho-Pérula E, Irwin DJ, Ittyerah R, Lee EB, Lim S, Marcos-Rabal MDP, Martin MMIDO, Lopez MM, Prieto CDLR, Schuck T, Trotman W, Vela A, Yushkevich P, Amunts K, Augustinack JC, Ding SL, Insausti R, Kedo O, Berron D, Wisse LEM. Comparison of histological delineations of medial temporal lobe cortices by four independent neuroanatomy laboratories. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.05.24.542054. [PMID: 37292729 PMCID: PMC10245880 DOI: 10.1101/2023.05.24.542054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
The medial temporal lobe (MTL) cortex, located adjacent to the hippocampus, is crucial for memory and prone to the accumulation of certain neuropathologies such as Alzheimer's disease neurofibrillary tau tangles. The MTL cortex is composed of several subregions which differ in their functional and cytoarchitectonic features. As neuroanatomical schools rely on different cytoarchitectonic definitions of these subregions, it is unclear to what extent their delineations of MTL cortex subregions overlap. Here, we provide an overview of cytoarchitectonic definitions of the cortices that make up the parahippocampal gyrus (entorhinal and parahippocampal cortices) and the adjacent Brodmann areas (BA) 35 and 36, as provided by four neuroanatomists from different laboratories, aiming to identify the rationale for overlapping and diverging delineations. Nissl-stained series were acquired from the temporal lobes of three human specimens (two right and one left hemisphere). Slices (50 µm thick) were prepared perpendicular to the long axis of the hippocampus spanning the entire longitudinal extent of the MTL cortex. Four neuroanatomists annotated MTL cortex subregions on digitized (20X resolution) slices with 5 mm spacing. Parcellations, terminology, and border placement were compared among neuroanatomists. Cytoarchitectonic features of each subregion are described in detail. Qualitative analysis of the annotations showed higher agreement in the definitions of the entorhinal cortex and BA35, while definitions of BA36 and the parahippocampal cortex exhibited less overlap among neuroanatomists. The degree of overlap of cytoarchitectonic definitions was partially reflected in the neuroanatomists' agreement on the respective delineations. Lower agreement in annotations was observed in transitional zones between structures where seminal cytoarchitectonic features are expressed more gradually. The results highlight that definitions and parcellations of the MTL cortex differ among neuroanatomical schools and thereby increase understanding of why these differences may arise. This work sets a crucial foundation to further advance anatomically-informed human neuroimaging research on the MTL cortex.
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Affiliation(s)
- Anika Wuestefeld
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
| | - Hannah Baumeister
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Jenna N Adams
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, USA
| | - Robin de Flores
- INSERM UMR-S U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain, Caen-Normandie University, Caen-Normandie, France
| | | | - Negar Mazloum-Farzaghi
- University of Toronto, Toronto, ON, Canada
- Rotman Research Institute, North York, ON, Canada
| | - Rosanna K Olsen
- University of Toronto, Toronto, ON, Canada
- Rotman Research Institute, North York, ON, Canada
| | - Vyash Puliyadi
- Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Tammy T Tran
- Department of Psychology, Stanford University, Stanford, CA, USA
| | - Arnold Bakker
- Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Kelsey L Canada
- Institute of Gerontology, Wayne State University, Detroit, MI, USA
| | | | - Ana M Daugherty
- Institute of Gerontology, Wayne State University, Detroit, MI, USA
- Department of Psychology, Wayne State University, Detroit, MI, USA
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco USA
| | - Lei Wang
- The Ohio State University, Columbus, OH, USA
| | - Madigan Bedard
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | | | - Eunice Chung
- University of Pennsylvania, Philadelphia, PA, USA
| | | | | | | | | | | | - Edward B Lee
- University of Pennsylvania, Philadelphia, PA, USA
| | - Sydney Lim
- University of Pennsylvania, Philadelphia, PA, USA
| | | | | | | | | | | | | | - Alicia Vela
- University of Castilla-La Mancha, Albacete, Spain
| | | | - Katrin Amunts
- Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany
- C. & O. Vogt Institute for Brain Research, Medical Faculty, University Hospital Düsseldorf, Heinrich-Heine-University, Düsseldorf, Germany
| | | | | | | | - Olga Kedo
- Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany
| | - David Berron
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
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Oltmer J, Greve DN, Cerri S, Slepneva N, Llamas-Rodríguez J, Iglesias JE, Van Leemput K, Champion SN, Frosch MP, Augustinack JC. Assessing individual variability of the entorhinal subfields in health and disease. J Comp Neurol 2023; 531:2062-2079. [PMID: 37700618 PMCID: PMC10841297 DOI: 10.1002/cne.25538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 07/31/2023] [Accepted: 08/23/2023] [Indexed: 09/14/2023]
Abstract
Investigating interindividual variability is a major field of interest in neuroscience. The entorhinal cortex (EC) is essential for memory and affected early in the progression of Alzheimer's disease (AD). We combined histology ground-truth data with ultrahigh-resolution 7T ex vivo MRI to analyze EC interindividual variability in 3D. Further, we characterized (1) entorhinal shape as a whole, (2) entorhinal subfield range and midpoints, and (3) subfield architectural location and tau burden derived from 3D probability maps. Our results indicated that EC shape varied but was not related to demographic or disease factors at this preclinical stage. The medial intermediate subfield showed the highest degree of location variability in the probability maps. However, individual subfields did not display the same level of variability across dimensions and outcome measure, each providing a different perspective. For example, the olfactory subfield showed low variability in midpoint location in the superior-inferior dimension but high variability in anterior-posterior, and the subfield entorhinal intermediate showed a large variability in volumetric measures but a low variability in location derived from the 3D probability maps. These findings suggest that interindividual variability within the entorhinal subfields requires a 3D approach incorporating multiple outcome measures. This study provides 3D probability maps of the individual entorhinal subfields and respective tau pathology in the preclinical stage (Braak I and II) of AD. These probability maps illustrate the subfield average and may serve as a checkpoint for future modeling.
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Affiliation(s)
- Jan Oltmer
- Athinoula A. Martinos Center, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
- Department of Digital Health & Innovation, Vivantes Netzwerk für Gesundheit GmbH, Berlin, Germany
| | - Douglas N Greve
- Athinoula A. Martinos Center, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Stefano Cerri
- Athinoula A. Martinos Center, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Natalya Slepneva
- Athinoula A. Martinos Center, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Josue Llamas-Rodríguez
- Athinoula A. Martinos Center, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Juan Eugenio Iglesias
- Athinoula A. Martinos Center, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
- Centre for Medical Image Computing, University College London, London, UK
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Koen Van Leemput
- Athinoula A. Martinos Center, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Department of Neuroscience and Biomedical Engineering, Aalto University, Helsinki, Finland
- Department of Computer Science, Aalto University, Helsinki, Finland
| | - Samantha N Champion
- Department of Neuropathology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Matthew P Frosch
- Department of Neuropathology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Jean C Augustinack
- Athinoula A. Martinos Center, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
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5
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Stouffer KM, Chen C, Kulason S, Xu E, Witter MP, Ceritoglu C, Albert MS, Mori S, Troncoso J, Tward DJ, Miller MI. Early amygdala and ERC atrophy linked to 3D reconstruction of rostral neurofibrillary tau tangle pathology in Alzheimer's disease. Neuroimage Clin 2023; 38:103374. [PMID: 36934675 PMCID: PMC10034129 DOI: 10.1016/j.nicl.2023.103374] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2022] [Revised: 03/07/2023] [Accepted: 03/08/2023] [Indexed: 03/17/2023]
Abstract
Previous research has emphasized the unique impact of Alzheimer's Disease (AD) pathology on the medial temporal lobe (MTL), a reflection that tau pathology is particularly striking in the entorhinal and transentorhinal cortex (ERC, TEC) early in the course of disease. However, other brain regions are affected by AD pathology during its early phases. Here, we use longitudinal diffeomorphometry to measure the atrophy rate from MRI of the amygdala compared with that in the ERC and TEC in cognitively unimpaired (CU) controls, CU individuals who progressed to mild cognitive impairment (MCI), and individuals with MCI who progressed to dementia of the AD type (DAT), using a dataset from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Our results show significantly higher atrophy rates of the amygdala in both groups of 'converters' (CU→MCI, MCI→DAT) compared to controls, with rates of volume loss comparable to rates of thickness loss in the ERC and TEC. We localize atrophy within the amygdala within each of these groups using fixed effects modeling. Controlling for the familywise error rate highlights the medial regions of the amygdala as those with significantly higher atrophy in both groups of converters than in controls. Using our recently developed method, referred to as Projective LDDMM, we map measures of neurofibrillary tau tangles (NFTs) from digital pathology to MRI atlases and reconstruct dense 3D spatial distributions of NFT density within regions of the MTL. The distribution of NFTs is consistent with the spatial distribution of MR measured atrophy rates, revealing high densities (and atrophy) in the amygdala (particularly medial), ERC, and rostral third of the MTL. The similarity of the location of NFTs in AD and shape changes in a well-defined clinical population suggests that amygdalar atrophy rate, as measured through MRI may be a viable biomarker for AD.
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Affiliation(s)
- Kaitlin M Stouffer
- Department of Biomedical Engineering, Johns Hopkins University, 3400 N Charles St, Baltimore 21218, MD, USA.
| | - Claire Chen
- Department of Biomedical Engineering, Johns Hopkins University, 3400 N Charles St, Baltimore 21218, MD, USA
| | - Sue Kulason
- Department of Biomedical Engineering, Johns Hopkins University, 3400 N Charles St, Baltimore 21218, MD, USA
| | - Eileen Xu
- Department of Biomedical Engineering, Johns Hopkins University, 3400 N Charles St, Baltimore 21218, MD, USA
| | - Menno P Witter
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, 7491 Trondheim, Norway
| | - Can Ceritoglu
- Department of Biomedical Engineering, Johns Hopkins University, 3400 N Charles St, Baltimore 21218, MD, USA
| | - Marilyn S Albert
- Departments of Neurology, Johns Hopkins School of Medicine, 733 N Broadway, Baltimore 21205, MD, USA
| | - Susumu Mori
- Department of Radiology, Johns Hopkins School of Medicine, 733 N Broadway, Baltimore 21205, MD, USA
| | - Juan Troncoso
- Department of Pathology, Johns Hopkins School of Medicine, 733 N Broadway, Baltimore 21205, MD, USA
| | - Daniel J Tward
- Departments of Computational Medicine and Neurology, University of California, Los Angeles, UCLA Brain Mapping Center, 660 Charles E. Young Drive South, Los Angeles 90095, CA, USA
| | - Michael I Miller
- Department of Biomedical Engineering, Johns Hopkins University, 3400 N Charles St, Baltimore 21218, MD, USA
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Williams EM, Rosenblum EW, Pihlstrom N, Llamas-Rodríguez J, Champion S, Frosch MP, Augustinack JC. Pentad: A reproducible cytoarchitectonic protocol and its application to parcellation of the human hippocampus. Front Neuroanat 2023; 17:1114757. [PMID: 36843959 PMCID: PMC9947247 DOI: 10.3389/fnana.2023.1114757] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 01/13/2023] [Indexed: 02/11/2023] Open
Abstract
Introduction The hippocampus is integral for learning and memory and is targeted by multiple diseases. Neuroimaging approaches frequently use hippocampal subfield volumes as a standard measure of neurodegeneration, thus making them an essential biomarker to study. Collectively, histologic parcellation studies contain various disagreements, discrepancies, and omissions. The present study aimed to advance the hippocampal subfield segmentation field by establishing the first histology based parcellation protocol, applied to n = 22 human hippocampal samples. Methods The protocol focuses on five cellular traits observed in the pyramidal layer of the human hippocampus. We coin this approach the pentad protocol. The traits were: chromophilia, neuron size, packing density, clustering, and collinearity. Subfields included were CA1, CA2, CA3, CA4, prosubiculum, subiculum, presubiculum, parasubiculum, as well as the medial (uncal) subfields Subu, CA1u, CA2u, CA3u, and CA4u. We also establish nine distinct anterior-posterior levels of the hippocampus in the coronal plane to document rostrocaudal differences. Results Applying the pentad protocol, we parcellated 13 subfields at nine levels in 22 samples. We found that CA1 had the smallest neurons, CA2 showed high neuronal clustering, and CA3 displayed the most collinear neurons of the CA fields. The border between presubiculum and subiculum was staircase shaped, and parasubiculum had larger neurons than presubiculum. We also demonstrate cytoarchitectural evidence that CA4 and prosubiculum exist as individual subfields. Discussion This protocol is comprehensive, regimented and supplies a high number of samples, hippocampal subfields, and anterior-posterior coronal levels. The pentad protocol utilizes the gold standard approach for the human hippocampus subfield parcellation.
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Affiliation(s)
- Emily M. Williams
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
| | - Emma W. Rosenblum
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
| | - Nicole Pihlstrom
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
| | - Josué Llamas-Rodríguez
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
| | - Samantha Champion
- Department of Neuropathology, Massachusetts General Hospital, Boston, MA, United States
| | - Matthew P. Frosch
- Department of Neuropathology, Massachusetts General Hospital, Boston, MA, United States
| | - Jean C. Augustinack
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
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7
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van Staalduinen EK, Zeineh MM. Medial Temporal Lobe Anatomy. Neuroimaging Clin N Am 2022; 32:475-489. [PMID: 35843657 DOI: 10.1016/j.nic.2022.04.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
The medial temporal lobe (MTL) is a complex anatomic region encompassing the hippocampal formation, parahippocampal region, and amygdaloid complex. To enable the reader to understand the well-studied regional anatomic relationships and cytoarchitecture that form the basis of functional connectivity, the authors have created a detailed yet approachable anatomic reference for clinicians and scientists, with special attention to MR imaging. They have focused primarily on the hippocampal formation, discussing its gross structural features, anatomic relationships, and subfield anatomy and further discuss hippocampal terminology and development, hippocampal connectivity, normal anatomic variants, clinically relevant disease processes, and automated hippocampal segmentation software.
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Affiliation(s)
| | - Michael M Zeineh
- Department of Radiology, Stanford University, 1201 Welch Road, Room P271, Stanford, CA 94305, USA.
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8
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Šimić G, Krsnik Ž, Knezović V, Kelović Z, Mathiasen ML, Junaković A, Radoš M, Mulc D, Španić E, Quattrocolo G, Hall VJ, Zaborszky L, Vukšić M, Olucha Bordonau F, Kostović I, Witter MP, Hof PR. Prenatal development of the human entorhinal cortex. J Comp Neurol 2022; 530:2711-2748. [DOI: 10.1002/cne.25344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 04/30/2022] [Accepted: 05/02/2022] [Indexed: 11/11/2022]
Affiliation(s)
- Goran Šimić
- Department of Neuroscience Croatian Institute for Brain Research University of Zagreb Medical School, Zagreb, HR Croatia
| | - Željka Krsnik
- Department of Neuroscience Croatian Institute for Brain Research University of Zagreb Medical School, Zagreb, HR Croatia
| | - Vinka Knezović
- Department of Neuroscience Croatian Institute for Brain Research University of Zagreb Medical School, Zagreb, HR Croatia
| | - Zlatko Kelović
- Department of Anatomy University of Zagreb Medical School, Zagreb, HR Croatia
| | - Mathias Lysholt Mathiasen
- Department of Veterinary and Animal Sciences Faculty of Health Sciences University of Copenhagen, Frederiksberg C, DK Denmark
| | - Alisa Junaković
- Department of Neuroscience Croatian Institute for Brain Research University of Zagreb Medical School, Zagreb, HR Croatia
| | - Milan Radoš
- Department of Neuroscience Croatian Institute for Brain Research University of Zagreb Medical School, Zagreb, HR Croatia
| | - Damir Mulc
- Psychiatric Hospital Vrapče University of Zagreb Medical School, Zagreb, HR Croatia
| | - Ena Španić
- Department of Neuroscience Croatian Institute for Brain Research University of Zagreb Medical School, Zagreb, HR Croatia
| | - Giulia Quattrocolo
- Kavli Institute for Systems Neuroscience and Centre for Neural Computation Norwegian University of Science and Technology Trondheim NO Norway
| | - Vanessa Jane Hall
- Department of Veterinary and Animal Sciences Faculty of Health Sciences University of Copenhagen, Frederiksberg C, DK Denmark
| | - Laszlo Zaborszky
- Center for Molecular and Behavioral Neuroscience Rutgers, The State University of New Jersey Newark New Jersey USA
| | - Mario Vukšić
- Department of Neuroscience Croatian Institute for Brain Research University of Zagreb Medical School, Zagreb, HR Croatia
| | - Francisco Olucha Bordonau
- Department of Medicine School of Medical Sciences Universitat Jaume I Castellón de la Plana ES Spain
| | - Ivica Kostović
- Department of Neuroscience Croatian Institute for Brain Research University of Zagreb Medical School, Zagreb, HR Croatia
| | - Menno P. Witter
- Kavli Institute for Systems Neuroscience and Centre for Neural Computation Norwegian University of Science and Technology Trondheim NO Norway
| | - Patrick R. Hof
- Nash Family Department of Neuroscience and Friedman Brain Institute Icahn School of Medicine at Mount Sinai New York New York USA
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9
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Oltmer J, Slepneva N, Llamas Rodriguez J, Greve DN, Williams EM, Wang R, Champion SN, Lang-Orsini M, Nestor K, Fernandez-Ros N, Fischl B, Frosch MP, Magnain C, van der Kouwe AJW, Augustinack JC. Quantitative and histologically validated measures of the entorhinal subfields in ex vivo MRI. Brain Commun 2022; 4:fcac074. [PMID: 35620167 PMCID: PMC9128374 DOI: 10.1093/braincomms/fcac074] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 01/04/2022] [Accepted: 03/17/2022] [Indexed: 12/15/2022] Open
Abstract
Neuroimaging studies have routinely used hippocampal volume as a measure of Alzheimer's disease severity, but hippocampal changes occur too late in the disease process for potential therapies to be effective. The entorhinal cortex is one of the first cortical areas affected by Alzheimer's disease; its neurons are especially vulnerable to neurofibrillary tangles. Entorhinal atrophy also relates to the conversion from non-clinical to clinical Alzheimer's disease. In neuroimaging, the human entorhinal cortex has so far mostly been considered in its entirety or divided into a medial and a lateral region. Cytoarchitectonic differences provide the opportunity for subfield parcellation. We investigated the entorhinal cortex on a subfield-specific level-at a critical time point of Alzheimer's disease progression. While MRI allows multidimensional quantitative measurements, only histology provides enough accuracy to determine subfield boundaries-the pre-requisite for quantitative measurements within the entorhinal cortex. This study used histological data to validate ultra-high-resolution 7 Tesla ex vivo MRI and create entorhinal subfield parcellations in a total of 10 pre-clinical Alzheimer's disease and normal control cases. Using ex vivo MRI, eight entorhinal subfields (olfactory, rostral, medial intermediate, intermediate, lateral rostral, lateral caudal, caudal, and caudal limiting) were characterized for cortical thickness, volume, and pial surface area. Our data indicated no influence of sex, or Braak and Braak staging on volume, cortical thickness, or pial surface area. The volume and pial surface area for mean whole entorhinal cortex were 1131 ± 55.72 mm3 and 429 ± 22.6 mm2 (mean ± SEM), respectively. The subfield volume percentages relative to the entire entorhinal cortex were olfactory: 18.73 ± 1.82%, rostral: 14.06 ± 0.63%, lateral rostral: 14.81 ± 1.22%, medial intermediate: 6.72 ± 0.72%, intermediate: 23.36 ± 1.85%, lateral caudal: 5.42 ± 0.33%, caudal: 10.99 ± 1.02%, and caudal limiting: 5.91 ± 0.40% (all mean ± SEM). Olfactory and intermediate subfield revealed the most extensive intra-individual variability (cross-subject variance) in volume and pial surface area. This study provides validated measures. It maps individuality and demonstrates human variability in the entorhinal cortex, providing a baseline for approaches in individualized medicine. Taken together, this study serves as a ground-truth validation study for future in vivo comparisons and treatments.
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Affiliation(s)
- Jan Oltmer
- Department of Radiology, Athinoula A. Martinos
Center, Massachusetts General Hospital, Charlestown, MA, USA,Harvard Medical School, Boston, MA,
USA
| | - Natalya Slepneva
- Department of Radiology, Athinoula A. Martinos
Center, Massachusetts General Hospital, Charlestown, MA, USA
| | - Josue Llamas Rodriguez
- Department of Radiology, Athinoula A. Martinos
Center, Massachusetts General Hospital, Charlestown, MA, USA
| | - Douglas N. Greve
- Department of Radiology, Athinoula A. Martinos
Center, Massachusetts General Hospital, Charlestown, MA, USA,Harvard Medical School, Boston, MA,
USA
| | - Emily M. Williams
- Department of Radiology, Athinoula A. Martinos
Center, Massachusetts General Hospital, Charlestown, MA, USA
| | - Ruopeng Wang
- Department of Radiology, Athinoula A. Martinos
Center, Massachusetts General Hospital, Charlestown, MA, USA
| | | | - Melanie Lang-Orsini
- Department of Neuropathology, Massachusetts General
Hospital, Boston, MA, USA
| | - Kimberly Nestor
- Department of Radiology, Athinoula A. Martinos
Center, Massachusetts General Hospital, Charlestown, MA, USA
| | - Nídia Fernandez-Ros
- Department of Radiology, Athinoula A. Martinos
Center, Massachusetts General Hospital, Charlestown, MA, USA
| | - Bruce Fischl
- Department of Radiology, Athinoula A. Martinos
Center, Massachusetts General Hospital, Charlestown, MA, USA,Harvard Medical School, Boston, MA,
USA,CSAIL, Cambridge, MA, USA
| | - Matthew P. Frosch
- Department of Neuropathology, Massachusetts General
Hospital, Boston, MA, USA
| | - Caroline Magnain
- Department of Radiology, Athinoula A. Martinos
Center, Massachusetts General Hospital, Charlestown, MA, USA,Harvard Medical School, Boston, MA,
USA
| | - Andre J. W. van der Kouwe
- Department of Radiology, Athinoula A. Martinos
Center, Massachusetts General Hospital, Charlestown, MA, USA,Harvard Medical School, Boston, MA,
USA
| | - Jean C. Augustinack
- Department of Radiology, Athinoula A. Martinos
Center, Massachusetts General Hospital, Charlestown, MA, USA,Harvard Medical School, Boston, MA,
USA,Correspondence to: Jean C. Augustinack Department of
Radiology Athinoula A. Martinos Center for Biomedical Imaging Massachusetts
General Hospital Building 149, 13th St Room 2301 Charlestown, MA 02129, USA
E-mail:
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10
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Zachlod D, Kedo O, Amunts K. Anatomy of the temporal lobe: From macro to micro. HANDBOOK OF CLINICAL NEUROLOGY 2022; 187:17-51. [PMID: 35964970 DOI: 10.1016/b978-0-12-823493-8.00009-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The temporal cortex encompasses a large number of different areas ranging from the six-layered isocortex to the allocortex. The areas support auditory, visual, and language processing, as well as emotions and memory. The primary auditory cortex is found at the Heschl gyri, which develop early in ontogeny with the Sylvian fissure, a deep and characteristic fissure that separates the temporal lobe from the parietal and frontal lobes. Gyri and sulci as well as brain areas vary between brains and between hemispheres, partly linked to the functional organization of language and lateralization. Interindividual variability in anatomy makes a direct comparison between different brains in structure-functional analysis often challenging, but can be addressed by applying cytoarchitectonic probability maps of the Julich-Brain atlas. We review the macroanatomy of the temporal lobe, its variability and asymmetry at the macro- and the microlevel, discuss the relationship to brain areas and their microstructure, and emphasize the advantage of a multimodal approach to address temporal lobe organization. We review recent data on combined cytoarchitectonic and molecular architectonic studies of temporal areas, and provide links to their function.
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Affiliation(s)
- Daniel Zachlod
- Institute of Neuroscience and Medicine, INM-1, Research Centre Juelich, Juelich, Germany
| | - Olga Kedo
- Institute of Neuroscience and Medicine, INM-1, Research Centre Juelich, Juelich, Germany
| | - Katrin Amunts
- Institute of Neuroscience and Medicine, INM-1, Research Centre Juelich, Juelich, Germany; C&O Vogt Institute for Brain Research, University Hospital Düsseldorf, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany.
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11
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Wang DX, Schmitt K, Seger S, Davila CE, Lega BC. Cross-regional phase amplitude coupling supports the encoding of episodic memories. Hippocampus 2021; 31:481-492. [PMID: 33544408 DOI: 10.1002/hipo.23309] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Revised: 12/21/2020] [Accepted: 01/23/2021] [Indexed: 11/10/2022]
Abstract
Phase amplitude coupling (PAC) between theta and gamma oscillations represents a key neurophysiological mechanism that promotes the temporal organization of oscillatory activity. For this reason, PAC has been implicated in item/context integration for episodic processes, including coordinating activity across multiple cortical regions. While data in humans has focused principally on PAC within a single brain region, data in rodents has revealed evidence that the phase of the hippocampal theta oscillation modulates gamma oscillations in the cortex (and vice versa). This pattern, termed cross-regional PAC (xPAC), has not previously been observed in human subjects engaged in mnemonic processing. We use a unique dataset with intracranial electrodes inserted simultaneously into the hippocampus and seven cortical regions across 40 human subjects to (1) test for the presence of significant cross-regional PAC (xPAC), (2) to establish that the magnitude of xPAC predicts memory encoding success, (3) to describe specific frequencies within the broad 2-9 Hz theta range that govern hippocampal-cortical interactions in xPAC, and (4) compare anterior versus posterior hippocampal xPAC patterns. We find that strong functional xPAC occurs principally between the hippocampus and other mesial temporal structures, namely entorhinal and parahippocampal cortices, and that xPAC is overall stronger for posterior hippocampal connections. We also show that our results are not confounded by alternative factors such as inter-regional phase synchrony, local PAC occurring within cortical regions, or artifactual theta oscillatory waveforms.
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Affiliation(s)
- David X Wang
- Department of Electrical and Computer Engineering, Southern Methodist University, Dallas, Texas, USA
| | - Kelsey Schmitt
- Department of Neurological Surgery, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Sarah Seger
- Department of Neurological Surgery, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Carlos E Davila
- Department of Electrical and Computer Engineering, Southern Methodist University, Dallas, Texas, USA
| | - Bradley C Lega
- Department of Neurological Surgery, University of Texas Southwestern Medical Center, Dallas, Texas, USA
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12
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Hallab A, Lange C, Apostolova I, Özden C, Gonzalez-Escamilla G, Klutmann S, Brenner W, Grothe MJ, Buchert R. Impairment of Everyday Spatial Navigation Abilities in Mild Cognitive Impairment Is Weakly Associated with Reduced Grey Matter Volume in the Medial Part of the Entorhinal Cortex. J Alzheimers Dis 2020; 78:1149-1159. [PMID: 33104026 DOI: 10.3233/jad-200520] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Research in rodents identified specific neuron populations encoding information for spatial navigation with particularly high density in the medial part of the entorhinal cortex (ERC), which may be homologous with Brodmann area 34 (BA34) in the human brain. OBJECTIVE The aim of this study was to test whether impaired spatial navigation frequently occurring in mild cognitive impairment (MCI) is specifically associated with neurodegeneration in BA34. METHODS The study included baseline data of MCI patients enrolled in the Alzheimer's Disease Neuroimaging Initiative with high-resolution structural MRI, brain FDG PET, and complete visuospatial ability scores of the Everyday Cognition test (VS-ECog) within 30 days of PET. A standard mask of BA34 predefined in MNI space was mapped to individual native space to determine grey matter volume and metabolic activity in BA34 on MRI and on (partial volume corrected) FDG PET, respectively. The association of the VS-ECog sum score with grey matter volume and metabolic activity in BA34, APOE4 carrier status, age, education, and global cognition (ADAS-cog-13 score) was tested by linear regression. BA28, which constitutes the lateral part of the ERC, was used as control region. RESULTS The eligibility criteria led to inclusion of 379 MCI subjects. The VS-ECog sum score was negatively correlated with grey matter volume in BA34 (β= -0.229, p = 0.022) and age (β= -0.124, p = 0.036), and was positively correlated with ADAS-cog-13 (β= 0.175, p = 0.003). None of the other predictor variables contributed significantly. CONCLUSION Impairment of spatial navigation in MCI is weakly associated with BA34 atrophy.
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Affiliation(s)
- Asma Hallab
- Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Catharina Lange
- Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Ivayla Apostolova
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Cansu Özden
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Gabriel Gonzalez-Escamilla
- German Center for Neurodegenerative Diseases (DZNE), Rostock/Greifswald, Rostock, Germany.,Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Susanne Klutmann
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Winfried Brenner
- Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Michel J Grothe
- German Center for Neurodegenerative Diseases (DZNE), Rostock/Greifswald, Rostock, Germany.,Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville, Spain
| | - Ralph Buchert
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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