0
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Adults vs. neonates: Differentiation of functional connectivity between the basolateral amygdala and occipitotemporal cortex

      research-article
      * , , *
      PLoS ONE
      Public Library of Science

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The amygdala, a subcortical structure known for social and emotional processing, consists of multiple subnuclei with unique functions and connectivity patterns. Tracer studies in adult macaques have shown that the basolateral subnuclei differentially connect to parts of visual cortex, with stronger connections to anterior regions and weaker connections to posterior regions; infant macaques show robust connectivity even with posterior visual regions. Do these developmental differences also exist in the human amygdala, and are there specific functional regions that undergo the most pronounced developmental changes in their connections with the amygdala? To address these questions, we explored the functional connectivity (from resting-state fMRI data) of the basolateral amygdala to occipitotemporal cortex in human neonates scanned within one week of life and compared the connectivity patterns to those observed in young adults. Specifically, we calculated amygdala connectivity to anterior-posterior gradients of the anatomically-defined occipitotemporal cortex, and also to putative occipitotemporal functional parcels, including primary and high-level visual and auditory cortices (V1, A1, face, scene, object, body, high-level auditory regions). Results showed a decreasing gradient of functional connectivity to the occipitotemporal cortex in adults–similar to the gradient seen in macaque tracer studies–but no such gradient was observed in neonates. Further, adults had stronger connections to high-level functional regions associated with face, body, and object processing, and weaker connections to primary sensory regions (i.e., A1, V1), whereas neonates showed the same amount of connectivity to primary and high-level sensory regions. Overall, these results show that functional connectivity between the amygdala and occipitotemporal cortex is not yet differentiated in neonates, suggesting a role of maturation and experience in shaping these connections later in life.

          Related collections

          Most cited references76

          • Record: found
          • Abstract: found
          • Article: not found

          An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.

          In this study, we have assessed the validity and reliability of an automated labeling system that we have developed for subdividing the human cerebral cortex on magnetic resonance images into gyral based regions of interest (ROIs). Using a dataset of 40 MRI scans we manually identified 34 cortical ROIs in each of the individual hemispheres. This information was then encoded in the form of an atlas that was utilized to automatically label ROIs. To examine the validity, as well as the intra- and inter-rater reliability of the automated system, we used both intraclass correlation coefficients (ICC), and a new method known as mean distance maps, to assess the degree of mismatch between the manual and the automated sets of ROIs. When compared with the manual ROIs, the automated ROIs were highly accurate, with an average ICC of 0.835 across all of the ROIs, and a mean distance error of less than 1 mm. Intra- and inter-rater comparisons yielded little to no difference between the sets of ROIs. These findings suggest that the automated method we have developed for subdividing the human cerebral cortex into standard gyral-based neuroanatomical regions is both anatomically valid and reliable. This method may be useful for both morphometric and functional studies of the cerebral cortex as well as for clinical investigations aimed at tracking the evolution of disease-induced changes over time, including clinical trials in which MRI-based measures are used to examine response to treatment.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            The minimal preprocessing pipelines for the Human Connectome Project.

            The Human Connectome Project (HCP) faces the challenging task of bringing multiple magnetic resonance imaging (MRI) modalities together in a common automated preprocessing framework across a large cohort of subjects. The MRI data acquired by the HCP differ in many ways from data acquired on conventional 3 Tesla scanners and often require newly developed preprocessing methods. We describe the minimal preprocessing pipelines for structural, functional, and diffusion MRI that were developed by the HCP to accomplish many low level tasks, including spatial artifact/distortion removal, surface generation, cross-modal registration, and alignment to standard space. These pipelines are specially designed to capitalize on the high quality data offered by the HCP. The final standard space makes use of a recently introduced CIFTI file format and the associated grayordinate spatial coordinate system. This allows for combined cortical surface and subcortical volume analyses while reducing the storage and processing requirements for high spatial and temporal resolution data. Here, we provide the minimum image acquisition requirements for the HCP minimal preprocessing pipelines and additional advice for investigators interested in replicating the HCP's acquisition protocols or using these pipelines. Finally, we discuss some potential future improvements to the pipelines. Copyright © 2013 Elsevier Inc. All rights reserved.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              The WU-Minn Human Connectome Project: an overview.

              The Human Connectome Project consortium led by Washington University, University of Minnesota, and Oxford University is undertaking a systematic effort to map macroscopic human brain circuits and their relationship to behavior in a large population of healthy adults. This overview article focuses on progress made during the first half of the 5-year project in refining the methods for data acquisition and analysis. Preliminary analyses based on a finalized set of acquisition and preprocessing protocols demonstrate the exceptionally high quality of the data from each modality. The first quarterly release of imaging and behavioral data via the ConnectomeDB database demonstrates the commitment to making HCP datasets freely accessible. Altogether, the progress to date provides grounds for optimism that the HCP datasets and associated methods and software will become increasingly valuable resources for characterizing human brain connectivity and function, their relationship to behavior, and their heritability and genetic underpinnings. Copyright © 2013 Elsevier Inc. All rights reserved.
                Bookmark

                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: VisualizationRole: Writing – original draft
                Role: Data curationRole: Formal analysisRole: MethodologyRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: SupervisionRole: VisualizationRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                19 October 2020
                2020
                : 15
                : 10
                : e0237204
                Affiliations
                [001]Department of Psychology, The Ohio State University, Columbus, Ohio, United States of America
                Universidad de Chile, CHILE
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0002-8917-2516
                Article
                PONE-D-20-22317
                10.1371/journal.pone.0237204
                7571669
                33075046
                d60d1438-6ede-4ab9-b84f-738920d38b57
                © 2020 Hansen et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 18 July 2020
                : 5 October 2020
                Page count
                Figures: 3, Tables: 0, Pages: 17
                Funding
                Financial support was provided by the Alfred P. Sloan Foundation (to Z.M.S) and Ohio State’s Chronic Brain Injury Program (to Z.M.S). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Anatomy
                Brain
                Amygdala
                Medicine and Health Sciences
                Anatomy
                Brain
                Amygdala
                Biology and life sciences
                Organisms
                Eukaryota
                Animals
                Vertebrates
                Amniotes
                Mammals
                Primates
                Monkeys
                Old World monkeys
                Macaque
                Biology and life sciences
                Zoology
                Animals
                Vertebrates
                Amniotes
                Mammals
                Primates
                Monkeys
                Old World monkeys
                Macaque
                Biology and Life Sciences
                Neuroscience
                Cognitive Science
                Cognitive Psychology
                Perception
                Sensory Perception
                Vision
                Biology and Life Sciences
                Psychology
                Cognitive Psychology
                Perception
                Sensory Perception
                Vision
                Social Sciences
                Psychology
                Cognitive Psychology
                Perception
                Sensory Perception
                Vision
                Biology and Life Sciences
                Neuroscience
                Sensory Perception
                Vision
                Biology and Life Sciences
                Psychology
                Emotions
                Social Sciences
                Psychology
                Emotions
                Biology and Life Sciences
                Developmental Biology
                Neonates
                Biology and Life Sciences
                Neuroscience
                Cognitive Science
                Cognitive Psychology
                Perception
                Sensory Perception
                Biology and Life Sciences
                Psychology
                Cognitive Psychology
                Perception
                Sensory Perception
                Social Sciences
                Psychology
                Cognitive Psychology
                Perception
                Sensory Perception
                Biology and Life Sciences
                Neuroscience
                Sensory Perception
                Computer and Information Sciences
                Software Engineering
                Preprocessing
                Engineering and Technology
                Software Engineering
                Preprocessing
                Biology and Life Sciences
                Neuroscience
                Brain Mapping
                Functional Magnetic Resonance Imaging
                Medicine and Health Sciences
                Diagnostic Medicine
                Diagnostic Radiology
                Magnetic Resonance Imaging
                Functional Magnetic Resonance Imaging
                Research and Analysis Methods
                Imaging Techniques
                Diagnostic Radiology
                Magnetic Resonance Imaging
                Functional Magnetic Resonance Imaging
                Medicine and Health Sciences
                Radiology and Imaging
                Diagnostic Radiology
                Magnetic Resonance Imaging
                Functional Magnetic Resonance Imaging
                Research and Analysis Methods
                Imaging Techniques
                Neuroimaging
                Functional Magnetic Resonance Imaging
                Biology and Life Sciences
                Neuroscience
                Neuroimaging
                Functional Magnetic Resonance Imaging
                Custom metadata
                The data used in this study are publicly available. All relevant accession codes are publicly available for both HCP ( https://www.humanconnectome.org/study/hcp-young-adult) and dHCP ( http://www.developingconnectome.org/)

                Uncategorized
                Uncategorized

                Comments

                Comment on this article