51
|
Keifer OP, Gutman DA, Hecht EE, Keilholz SD, Ressler KJ. A comparative analysis of mouse and human medial geniculate nucleus connectivity: a DTI and anterograde tracing study. Neuroimage 2014; 105:53-66. [PMID: 25450110 DOI: 10.1016/j.neuroimage.2014.10.047] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2014] [Revised: 10/16/2014] [Accepted: 10/19/2014] [Indexed: 01/16/2023] Open
Abstract
Understanding the function and connectivity of thalamic nuclei is critical for understanding normal and pathological brain function. The medial geniculate nucleus (MGN) has been studied mostly in the context of auditory processing and its connection to the auditory cortex. However, there is a growing body of evidence that the MGN and surrounding associated areas ('MGN/S') have a diversity of projections including those to the globus pallidus, caudate/putamen, amygdala, hypothalamus, and thalamus. Concomitantly, pathways projecting to the medial geniculate include not only the inferior colliculus but also the auditory cortex, insula, cerebellum, and globus pallidus. Here we expand our understanding of the connectivity of the MGN/S by using comparative diffusion weighted imaging with probabilistic tractography in both human and mouse brains (most previous work was in rats). In doing so, we provide the first report that attempts to match probabilistic tractography results between human and mice. Additionally, we provide anterograde tracing results for the mouse brain, which corroborate the probabilistic tractography findings. Overall, the study provides evidence for the homology of MGN/S patterns of connectivity across species for understanding translational approaches to thalamic connectivity and function. Further, it points to the utility of DTI in both human studies and small animal modeling, and it suggests potential roles of these connections in human cognition, behavior, and disease.
Collapse
Affiliation(s)
- Orion P Keifer
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA; Yerkes National Primate Research Center, Atlanta, GA, USA
| | - David A Gutman
- Department of Biomedical Informatics, Emory University, Atlanta, GA, USA
| | - Erin E Hecht
- Department of Anthropology, Emory University, Atlanta, GA, USA
| | - Shella D Keilholz
- Coulter Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Kerry J Ressler
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA; Howard Hughes Medical Institute, Chevy Chase, MD, USA; Yerkes National Primate Research Center, Atlanta, GA, USA.
| |
Collapse
|
52
|
Amunts K, Hawrylycz MJ, Van Essen DC, Van Horn JD, Harel N, Poline JB, De Martino F, Bjaalie JG, Dehaene-Lambertz G, Dehaene S, Valdes-Sosa P, Thirion B, Zilles K, Hill SL, Abrams MB, Tass PA, Vanduffel W, Evans AC, Eickhoff SB. Interoperable atlases of the human brain. Neuroimage 2014; 99:525-32. [PMID: 24936682 DOI: 10.1016/j.neuroimage.2014.06.010] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2014] [Revised: 05/05/2014] [Accepted: 06/02/2014] [Indexed: 12/11/2022] Open
Abstract
The last two decades have seen an unprecedented development of human brain mapping approaches at various spatial and temporal scales. Together, these have provided a large fundus of information on many different aspects of the human brain including micro- and macrostructural segregation, regional specialization of function, connectivity, and temporal dynamics. Atlases are central in order to integrate such diverse information in a topographically meaningful way. It is noteworthy, that the brain mapping field has been developed along several major lines such as structure vs. function, postmortem vs. in vivo, individual features of the brain vs. population-based aspects, or slow vs. fast dynamics. In order to understand human brain organization, however, it seems inevitable that these different lines are integrated and combined into a multimodal human brain model. To this aim, we held a workshop to determine the constraints of a multi-modal human brain model that are needed to enable (i) an integration of different spatial and temporal scales and data modalities into a common reference system, and (ii) efficient data exchange and analysis. As detailed in this report, to arrive at fully interoperable atlases of the human brain will still require much work at the frontiers of data acquisition, analysis, and representation. Among them, the latter may provide the most challenging task, in particular when it comes to representing features of vastly different scales of space, time and abstraction. The potential benefits of such endeavor, however, clearly outweigh the problems, as only such kind of multi-modal human brain atlas may provide a starting point from which the complex relationships between structure, function, and connectivity may be explored.
Collapse
Affiliation(s)
- K Amunts
- Institute of Neuroscience and Medicine, INM-1, Research Centre Jülich, Germany; C. and O. Vogt Institute for Brain Research, Heinrich Heine University, Düsseldorf, Germany
| | | | - D C Van Essen
- Department of Anatomy and Neurobiology, Washington University School of Medicine, St. Louis, MO, USA
| | - J D Van Horn
- The Institute for Neuroimaging and Informatics (INI) and Laboratory for Neuro Imaging (LONI), Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - N Harel
- Center for Magnetic Resonance Research, Departments of Radiology & Neurosurgery, University of Minnesota School of Medicine, Minneapolis, MN, USA
| | - J-B Poline
- Hellen Wills Neuroscience Institute, Brain Imaging Center, University of California at Berkeley, CA, USA
| | - F De Martino
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - J G Bjaalie
- Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | | | - S Dehaene
- INSERM, U992, Cognitive Neuroimaging Unit, F-91191 Gif/Yvette, France
| | - P Valdes-Sosa
- Cuban Neuroscience Center, Havana, Cuba; Key Laboratory for Neuroinformation, Chengudu, China
| | - B Thirion
- Parietal Research Team, French Institute for Research in Computer Science and Automation (INRIA), Gif sur Yvette, France
| | - K Zilles
- Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH University Aachen, Aachen, Germany; Jülich-Aachen Research Alliance (JARA), Translational Brain Medicine, Jülich, Germany
| | - S L Hill
- International Neuroinformatics Coordinating Facility Secretariat (INCF), Stockholm, Sweden
| | - M B Abrams
- International Neuroinformatics Coordinating Facility Secretariat (INCF), Stockholm, Sweden.
| | - P A Tass
- Institute of Neuroscience and Medicine, INM-1, Research Centre Jülich, Germany; Department of Neuromodulation, University of Cologne, Cologne, Germany; Department of Neurosurgery, Stanford University, Stanford, USA
| | - W Vanduffel
- Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - A C Evans
- Montreal Neurological Institute, McGill University, Montreal, Canada
| | - S B Eickhoff
- Institute of Neuroscience and Medicine, INM-1, Research Centre Jülich, Germany; Institute for Clinical Neuroscience and Medical Psychology, Heinrich-Heine University, Düsseldorf, Germany
| |
Collapse
|