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Caspar KR, Gutiérrez-Ibáñez C, Bertrand OC, Carr T, Colbourne JAD, Erb A, George H, Holtz TR, Naish D, Wylie DR, Hurlburt GR. How smart was T. rex? Testing claims of exceptional cognition in dinosaurs and the application of neuron count estimates in palaeontological research. Anat Rec (Hoboken) 2024; 307:3685-3716. [PMID: 38668805 DOI: 10.1002/ar.25459] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2024] [Revised: 04/03/2024] [Accepted: 04/07/2024] [Indexed: 11/07/2024]
Abstract
Recent years have seen increasing scientific interest in whether neuron counts can act as correlates of diverse biological phenomena. Lately, Herculano-Houzel (2023) argued that fossil endocasts and comparative neurological data from extant sauropsids allow to reconstruct telencephalic neuron counts in Mesozoic dinosaurs and pterosaurs, which might act as proxies for behaviors and life history traits in these animals. According to this analysis, large theropods such as Tyrannosaurus rex were long-lived, exceptionally intelligent animals equipped with "macaque- or baboon-like cognition", whereas sauropods and most ornithischian dinosaurs would have displayed significantly smaller brains and an ectothermic physiology. Besides challenging established views on Mesozoic dinosaur biology, these claims raise questions on whether neuron count estimates could benefit research on fossil animals in general. Here, we address these findings by revisiting Herculano-Houzel's (2023) work, identifying several crucial shortcomings regarding analysis and interpretation. We present revised estimates of encephalization and telencephalic neuron counts in dinosaurs, which we derive from phylogenetically informed modeling and an amended dataset of endocranial measurements. For large-bodied theropods in particular, we recover significantly lower neuron counts than previously proposed. Furthermore, we review the suitability of neurological variables such as neuron numbers and relative brain size to predict cognitive complexity, metabolic rate and life history traits in dinosaurs, coming to the conclusion that they are flawed proxies for these biological phenomena. Instead of relying on such neurological estimates when reconstructing Mesozoic dinosaur biology, we argue that integrative studies are needed to approach this complex subject.
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Affiliation(s)
- Kai R Caspar
- Institute of Cell Biology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Department of Game Management and Wildlife Biology, Faculty of Forestry and Wood Sciences, Czech University of Life Sciences, Prague, Czech Republic
| | | | - Ornella C Bertrand
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, Barcelona, Spain
- Section of Mammals, Carnegie Museum of Natural History, Pittsburgh, Pennsylvania, USA
| | - Thomas Carr
- Department of Biology, Carthage College, Kenosha, Wisconsin, USA
| | - Jennifer A D Colbourne
- Comparative Cognition Unit, Messerli Research Institute, University of Veterinary Medicine Vienna, Vienna, Austria
| | - Arthur Erb
- School of GeoSciences, Grant Institute, University of Edinburgh, Edinburgh, UK
- Center for Science, Teaching, and Learning, Rockville Centre, New York, USA
| | - Hady George
- School of Earth Sciences, University of Bristol, Bristol, UK
| | - Thomas R Holtz
- Department of Geology, University of Maryland, College Park, Maryland, USA
- Department of Paleobiology, National Museum of Natural History, Washington, District of Columbia, USA
| | - Darren Naish
- School of Biological Sciences, Faculty of Environment and Life Sciences, University of Southampton, Southampton, UK
| | - Douglas R Wylie
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada
| | - Grant R Hurlburt
- Department of Natural History, Royal Ontario Museum, Toronto, Ontario, Canada
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2
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Zhao HT, Schmidt ER. Human-specific genetic modifiers of cortical architecture and function. Curr Opin Genet Dev 2024; 88:102241. [PMID: 39111228 PMCID: PMC11547859 DOI: 10.1016/j.gde.2024.102241] [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: 04/04/2024] [Revised: 06/30/2024] [Accepted: 07/23/2024] [Indexed: 09/11/2024]
Abstract
Evolution of the cerebral cortex is thought to have been critical for the emergence of our cognitive abilities. Major features of cortical evolution include increased neuron number and connectivity and altered morpho-electric properties of cortical neurons. Significant progress has been made in identifying human-specific genetic modifiers (HSGMs), some of which are involved in shaping these features of cortical architecture. But how did these evolutionary changes support the emergence of our cognitive abilities? Here, we highlight recent studies aimed at examining the impact of HSGMs on cortical circuit function and behavior. We also discuss the need for greater insight into the link between evolution of cortical architecture and the functional and computational properties of neuronal circuits, as we seek to provide a neurobiological foundation for human cognition.
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Affiliation(s)
- Hanzhi T Zhao
- Department of Neuroscience, Medical University of South Carolina, Suite 403 BSB, MSC510, 173 Ashley Ave, Charleston, SC 29425, USA
| | - Ewoud Re Schmidt
- Department of Neuroscience, Medical University of South Carolina, Suite 403 BSB, MSC510, 173 Ashley Ave, Charleston, SC 29425, USA.
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3
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Hao S, Zhu X, Huang Z, Yang Q, Liu H, Wu Y, Zhan Y, Dong Y, Li C, Wang H, Haasdijk E, Wu Z, Li S, Yan H, Zhu L, Guo S, Wang Z, Ye A, Lin Y, Cui L, Tan X, Liu H, Wang M, Chen J, Zhong Y, Du W, Wang G, Lai T, Cao M, Yang T, Xu Y, Li L, Yu Q, Zhuang Z, Xia Y, Lei Y, An Y, Cheng M, Zhao Y, Han L, Yuan Y, Song X, Song Y, Gu L, Liu C, Lin X, Wang R, Wang Z, Wang Y, Li S, Li H, Song J, Chen M, Zhou W, Yuan N, Sun S, Wang S, Chen Y, Zheng M, Fang J, Zhang R, Zhang S, Chai Q, Liu J, Wei W, He J, Zhou H, Sun Y, Liu Z, Liu C, Yao J, Liang Z, Xu X, Poo M, Li C, De Zeeuw CI, Shen Z, Liu Z, Liu L, Liu S, Sun Y, Liu C. Cross-species single-cell spatial transcriptomic atlases of the cerebellar cortex. Science 2024; 385:eado3927. [PMID: 39325889 DOI: 10.1126/science.ado3927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 08/14/2024] [Indexed: 09/28/2024]
Abstract
The molecular and cellular organization of the primate cerebellum remains poorly characterized. We obtained single-cell spatial transcriptomic atlases of macaque, marmoset, and mouse cerebella and identified primate-specific cell subtypes, including Purkinje cells and molecular-layer interneurons, that show different expression of the glutamate ionotropic receptor Delta type subunit 2 (GRID2) gene. Distinct gene expression profiles were found in anterior, posterior, and vestibular regions in all species, whereas region-selective gene expression was predominantly observed in the granular layer of primates and in the Purkinje layer of mice. Gene expression gradients in the cerebellar cortex matched well with functional connectivity gradients revealed with awake functional magnetic resonance imaging, with more lobule-specific differences between primates and mice than between two primate species. These comprehensive atlases and comparative analyses provide the basis for understanding cerebellar evolution and function.
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Affiliation(s)
| | - Xiaojia Zhu
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Key Laboratory of Genetic Evolution & Animal Models, Chinese Academy of Sciences, Shanghai, 200031, China
- Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650201, China
| | - Zhi Huang
- BGI Research, Hangzhou 310030, China
- BGI Research, Shenzhen 518083, China
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China
| | - Qianqian Yang
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Hean Liu
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yan Wu
- BGI Research, Hangzhou 310030, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yafeng Zhan
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yu Dong
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
- Lingang Laboratory, Shanghai 200031, China
| | - Chao Li
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
| | - He Wang
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Elize Haasdijk
- Department of Neuroscience, Erasmus MC, 3015 GE Rotterdam, Netherlands
- Netherlands Institute for Neuroscience, Royal Academy of Arts and Sciences, 1105 BA Amsterdam, Netherlands
| | - Zihan Wu
- Tencent AI Lab, Shenzhen 518057, China
| | - Shenglong Li
- BGI Research, Hangzhou 310030, China
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China
| | - Haotian Yan
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Lijing Zhu
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
| | | | - Zefang Wang
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Aojun Ye
- University of Chinese Academy of Sciences, Beijing 100049, China
| | | | - Luman Cui
- BGI Research, Shenzhen 518083, China
| | - Xing Tan
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
| | | | - Mingli Wang
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
- Lingang Laboratory, Shanghai 200031, China
| | - Jing Chen
- China National GeneBank, BGI Research, Shenzhen 518120, China
| | - Yanqing Zhong
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Wensi Du
- China National GeneBank, BGI Research, Shenzhen 518120, China
| | - Guangling Wang
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Tingting Lai
- China National GeneBank, BGI Research, Shenzhen 518120, China
| | - Mengdi Cao
- Key Laboratory of Genetic Evolution & Animal Models, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Tao Yang
- China National GeneBank, BGI Research, Shenzhen 518120, China
| | - Yuanfang Xu
- Key Laboratory of Genetic Evolution & Animal Models, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Ling Li
- China National GeneBank, BGI Research, Shenzhen 518120, China
| | - Qian Yu
- Key Laboratory of Genetic Evolution & Animal Models, Chinese Academy of Sciences, Shanghai, 200031, China
| | | | - Ying Xia
- Key Laboratory of Genetic Evolution & Animal Models, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Ying Lei
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yingjie An
- Key Laboratory of Genetic Evolution & Animal Models, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Mengnan Cheng
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yun Zhao
- Key Laboratory of Genetic Evolution & Animal Models, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Lei Han
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yue Yuan
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Xinxiang Song
- Key Laboratory of Genetic Evolution & Animal Models, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yumo Song
- BGI Research, Shenzhen 518083, China
| | - Liqin Gu
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Chang Liu
- BGI Research, Shenzhen 518083, China
| | | | - Ruiqi Wang
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
| | | | - Yang Wang
- BGI Research, Shenzhen 518083, China
| | - Shenyu Li
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Huanhuan Li
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Jingjing Song
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Mengni Chen
- Key Laboratory of Genetic Evolution & Animal Models, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Wanqiu Zhou
- Key Laboratory of Genetic Evolution & Animal Models, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Nini Yuan
- Key Laboratory of Genetic Evolution & Animal Models, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Suhong Sun
- Key Laboratory of Genetic Evolution & Animal Models, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Shiwen Wang
- Key Laboratory of Genetic Evolution & Animal Models, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yu Chen
- Key Laboratory of Genetic Evolution & Animal Models, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Mingyuan Zheng
- Key Laboratory of Genetic Evolution & Animal Models, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Jiao Fang
- Key Laboratory of Genetic Evolution & Animal Models, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Ruiyi Zhang
- Key Laboratory of Genetic Evolution & Animal Models, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Shuzhen Zhang
- Key Laboratory of Genetic Evolution & Animal Models, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Qinwen Chai
- Key Laboratory of Genetic Evolution & Animal Models, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Jiabing Liu
- Key Laboratory of Genetic Evolution & Animal Models, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Wu Wei
- Lingang Laboratory, Shanghai 200031, China
| | - Jie He
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Haibo Zhou
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yangang Sun
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhen Liu
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Chuanyu Liu
- BGI Research, Hangzhou 310030, China
- BGI Research, Shenzhen 518083, China
- Shanxi Medical University-BGI Collaborative Center for Future Medicine, Shanxi Medical University, Taiyuan 030001, China
| | | | - Zhifeng Liang
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xun Xu
- BGI Research, Hangzhou 310030, China
- Shanxi Medical University-BGI Collaborative Center for Future Medicine, Shanxi Medical University, Taiyuan 030001, China
| | - Muming Poo
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai 201602, China
| | - Chengyu Li
- Lingang Laboratory, Shanghai 200031, China
| | - Chris I De Zeeuw
- Department of Neuroscience, Erasmus MC, 3015 GE Rotterdam, Netherlands
- Netherlands Institute for Neuroscience, Royal Academy of Arts and Sciences, 1105 BA Amsterdam, Netherlands
| | - Zhiming Shen
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai 201602, China
| | - Zhiyong Liu
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Longqi Liu
- BGI Research, Hangzhou 310030, China
- Shanxi Medical University-BGI Collaborative Center for Future Medicine, Shanxi Medical University, Taiyuan 030001, China
| | - Shiping Liu
- BGI Research, Hangzhou 310030, China
- BGI Research, Shenzhen 518083, China
| | - Yidi Sun
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Key Laboratory of Genetic Evolution & Animal Models, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Cirong Liu
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Key Laboratory of Genetic Evolution & Animal Models, Chinese Academy of Sciences, Shanghai, 200031, China
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4
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Karl MT, Kim YD, Rajendran K, Manger PR, Sherwood CC. Invariance of Mitochondria and Synapses in the Primary Visual Cortex of Mammals Provides Insight Into Energetics and Function. J Comp Neurol 2024; 532:e25669. [PMID: 39291629 PMCID: PMC11412485 DOI: 10.1002/cne.25669] [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: 02/10/2024] [Revised: 08/16/2024] [Accepted: 08/30/2024] [Indexed: 09/19/2024]
Abstract
The cerebral cortex accounts for substantial energy expenditure, primarily driven by the metabolic demands of synaptic signaling. Mitochondria, the organelles responsible for generating cellular energy, play a crucial role in this process. We investigated ultrastructural characteristics of the primary visual cortex in 18 phylogenetically diverse mammals, spanning a broad range of brain sizes from mouse to elephant. Our findings reveal remarkable uniformity in synapse density, postsynaptic density (PSD) length, and mitochondria density, indicating functional and metabolic constraints that maintain these fundamental features. Notably, we observed an average of 1.9 mitochondria per synapse across mammalian species. When considered together with the trend of decreasing neuron density with larger brain size, we find that brain enlargement in mammals is characterized by increasing proportions of synapses and mitochondria per cortical neuron. These results shed light on the adaptive mechanisms and metabolic dynamics that govern cortical ultrastructure across mammals.
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Affiliation(s)
- Molly T Karl
- Department of Anthropology and Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, District of Columbia, USA
- Department of Anatomy and Cell Biology, School of Medicine and Health Sciences, The George Washington University, Washington, District of Columbia, USA
| | - Young Do Kim
- Department of Anthropology and Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, District of Columbia, USA
| | - Kavita Rajendran
- Department of Anthropology and Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, District of Columbia, USA
| | - Paul R Manger
- Faculty of Health Sciences, School of Anatomical Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Chet C Sherwood
- Department of Anthropology and Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, District of Columbia, USA
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5
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Forcellati MR, Green TL, Watanabe A. Brain shapes of large-bodied, flightless ratites (Aves: Palaeognathae) emerge through distinct developmental allometries. ROYAL SOCIETY OPEN SCIENCE 2024; 11:240765. [PMID: 39263457 PMCID: PMC11387061 DOI: 10.1098/rsos.240765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/10/2024] [Revised: 07/27/2024] [Accepted: 07/31/2024] [Indexed: 09/13/2024]
Abstract
Comparative neuroanatomical studies have long debated the role of development in the evolution of novel and disparate brain morphologies. Historically, these studies have emphasized whether evolutionary shifts along conserved or distinct developmental allometric trends cause changes in brain morphologies. However, the degree to which interspecific differences between variably sized taxa originate through modifying developmental allometry remains largely untested. Taxa with disparate brain shapes and sizes thus allow for investigation into how developmental trends contribute to neuroanatomical diversification. Here, we examine a developmental series of large-bodied ratite birds (approx. 60-140 kg). We use three-dimensional geometric morphometrics on cephalic endocasts of common ostriches, emus and southern cassowaries and compare their developmental trajectories with those of the more modestly sized domestic chicken, previously shown to be in the same allometric grade as ratites. The results suggest that ratites and chickens exhibit disparate endocranial shapes not simply accounted for by their size differences. When shape and age are examined, chickens partly exhibit more accelerated and mature brain shapes than ratites of similar size and age. Taken together, our study indicates that disparate brain shapes between these differently sized taxa have emerged from the evolution of distinct developmental allometries, rather than simply following conserved scaling trends.
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Affiliation(s)
- Meghan R Forcellati
- Department of Ecology, Evolution, and Environmental Biology, Columbia University, New York, NY 10027, USA
- Richard Gilder Graduate School, American Museum of Natural History, New York, NY 10024, USA
| | - Todd L Green
- Biomedical and Anatomical Sciences, New York Institute of Technology, College of Osteopathic Medicine at Arkansas State University, Jonesboro, AR 72401, USA
- Department of Anatomy, New York Institute of Technology, College of Osteopathic Medicine, Old Westbury, NY 11568, USA
| | - Akinobu Watanabe
- Department of Anatomy, New York Institute of Technology, College of Osteopathic Medicine, Old Westbury, NY 11568, USA
- Division of Paleontology, American Museum of Natural History, New York, NY 10024, USA
- Life Sciences Department, Natural History Museum, London SW7 5BD, UK
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6
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Magrou L, Joyce MKP, Froudist-Walsh S, Datta D, Wang XJ, Martinez-Trujillo J, Arnsten AFT. The meso-connectomes of mouse, marmoset, and macaque: network organization and the emergence of higher cognition. Cereb Cortex 2024; 34:bhae174. [PMID: 38771244 PMCID: PMC11107384 DOI: 10.1093/cercor/bhae174] [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: 01/31/2024] [Revised: 03/29/2024] [Accepted: 04/08/2024] [Indexed: 05/22/2024] Open
Abstract
The recent publications of the inter-areal connectomes for mouse, marmoset, and macaque cortex have allowed deeper comparisons across rodent vs. primate cortical organization. In general, these show that the mouse has very widespread, "all-to-all" inter-areal connectivity (i.e. a "highly dense" connectome in a graph theoretical framework), while primates have a more modular organization. In this review, we highlight the relevance of these differences to function, including the example of primary visual cortex (V1) which, in the mouse, is interconnected with all other areas, therefore including other primary sensory and frontal areas. We argue that this dense inter-areal connectivity benefits multimodal associations, at the cost of reduced functional segregation. Conversely, primates have expanded cortices with a modular connectivity structure, where V1 is almost exclusively interconnected with other visual cortices, themselves organized in relatively segregated streams, and hierarchically higher cortical areas such as prefrontal cortex provide top-down regulation for specifying precise information for working memory storage and manipulation. Increased complexity in cytoarchitecture, connectivity, dendritic spine density, and receptor expression additionally reveal a sharper hierarchical organization in primate cortex. Together, we argue that these primate specializations permit separable deconstruction and selective reconstruction of representations, which is essential to higher cognition.
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Affiliation(s)
- Loïc Magrou
- Department of Neural Science, New York University, New York, NY 10003, United States
| | - Mary Kate P Joyce
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT 06510, United States
| | - Sean Froudist-Walsh
- School of Engineering Mathematics and Technology, University of Bristol, Bristol, BS8 1QU, United Kingdom
| | - Dibyadeep Datta
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06510, United States
| | - Xiao-Jing Wang
- Department of Neural Science, New York University, New York, NY 10003, United States
| | - Julio Martinez-Trujillo
- Departments of Physiology and Pharmacology, and Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, ON, N6A 3K7, Canada
| | - Amy F T Arnsten
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT 06510, United States
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7
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Farnworth MS, Montgomery SH. Evolution of neural circuitry and cognition. Biol Lett 2024; 20:20230576. [PMID: 38747685 PMCID: PMC11285921 DOI: 10.1098/rsbl.2023.0576] [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: 12/10/2023] [Revised: 03/08/2024] [Accepted: 03/26/2024] [Indexed: 05/25/2024] Open
Abstract
Neural circuits govern the interface between the external environment, internal cues and outwardly directed behaviours. To process multiple environmental stimuli and integrate these with internal state requires considerable neural computation. Expansion in neural network size, most readily represented by whole brain size, has historically been linked to behavioural complexity, or the predominance of cognitive behaviours. Yet, it is largely unclear which aspects of circuit variation impact variation in performance. A key question in the field of evolutionary neurobiology is therefore how neural circuits evolve to allow improved behavioural performance or innovation. We discuss this question by first exploring how volumetric changes in brain areas reflect actual neural circuit change. We explore three major axes of neural circuit evolution-replication, restructuring and reconditioning of cells and circuits-and discuss how these could relate to broader phenotypes and behavioural variation. This discussion touches on the relevant uses and limitations of volumetrics, while advocating a more circuit-based view of cognition. We then use this framework to showcase an example from the insect brain, the multi-sensory integration and internal processing that is shared between the mushroom bodies and central complex. We end by identifying future trends in this research area, which promise to advance the field of evolutionary neurobiology.
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Affiliation(s)
- Max S. Farnworth
- School of Biological Sciences, University of Bristol, Bristol, UK
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8
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Ye Z, Shelton AM, Shaker JR, Boussard J, Colonell J, Birman D, Manavi S, Chen S, Windolf C, Hurwitz C, Namima T, Pedraja F, Weiss S, Raducanu B, Ness TV, Jia X, Mastroberardino G, Rossi LF, Carandini M, Häusser M, Einevoll GT, Laurent G, Sawtell NB, Bair W, Pasupathy A, Lopez CM, Dutta B, Paninski L, Siegle JH, Koch C, Olsen SR, Harris TD, Steinmetz NA. Ultra-high density electrodes improve detection, yield, and cell type identification in neuronal recordings. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.08.23.554527. [PMID: 37662298 PMCID: PMC10473688 DOI: 10.1101/2023.08.23.554527] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
To understand the neural basis of behavior, it is essential to sensitively and accurately measure neural activity at single neuron and single spike resolution. Extracellular electrophysiology delivers this, but it has biases in the neurons it detects and it imperfectly resolves their action potentials. To minimize these limitations, we developed a silicon probe with much smaller and denser recording sites than previous designs, called Neuropixels Ultra (NP Ultra). This device samples neuronal activity at ultra-high spatial density (~10 times higher than previous probes) with low noise levels, while trading off recording span. NP Ultra is effectively an implantable voltage-sensing camera that captures a planar image of a neuron's electrical field. We use a spike sorting algorithm optimized for these probes to demonstrate that the yield of visually-responsive neurons in recordings from mouse visual cortex improves up to ~3-fold. We show that NP Ultra can record from small neuronal structures including axons and dendrites. Recordings across multiple brain regions and four species revealed a subset of extracellular action potentials with unexpectedly small spatial spread and axon-like features. We share a large-scale dataset of these brain-wide recordings in mice as a resource for studies of neuronal biophysics. Finally, using ground-truth identification of three major inhibitory cortical cell types, we found that these cell types were discriminable with approximately 75% success, a significant improvement over lower-resolution recordings. NP Ultra improves spike sorting performance, detection of subcellular compartments, and cell type classification to enable more powerful dissection of neural circuit activity during behavior.
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Affiliation(s)
- Zhiwen Ye
- Department of Biological Structure, University of Washington, Seattle, WA, USA
| | - Andrew M. Shelton
- MindScope Program, Allen Institute, Seattle, WA, USA
- Allen Institute for Neural Dynamics, Seattle, WA, USA
| | - Jordan R. Shaker
- Department of Biological Structure, University of Washington, Seattle, WA, USA
| | - Julien Boussard
- Department of Neuroscience, Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
| | | | - Daniel Birman
- Department of Biological Structure, University of Washington, Seattle, WA, USA
| | - Sahar Manavi
- MindScope Program, Allen Institute, Seattle, WA, USA
| | - Susu Chen
- Janelia Research Campus, Ashburn, VA, USA
| | - Charlie Windolf
- Department of Neuroscience, Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
| | - Cole Hurwitz
- Department of Neuroscience, Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
| | - Tomoyuki Namima
- Department of Biological Structure, University of Washington, Seattle, WA, USA
- Washington National Primate Research Center, Seattle, WA, USA
| | - Federico Pedraja
- Department of Neuroscience, Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
| | - Shahaf Weiss
- Max Planck Institute for Brain Research, Frankfurt, Germany
| | | | | | - Xiaoxuan Jia
- Center for Life Sciences & IDG/McGovern Institute for Brain Research, Tsinghua University, China
| | - Giulia Mastroberardino
- UCL Institute of Ophthalmology, University College London, London, UK
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - L. Federico Rossi
- Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Matteo Carandini
- UCL Institute of Ophthalmology, University College London, London, UK
| | - Michael Häusser
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Gaute T. Einevoll
- Norwegian University of Life Sciences, Ås, Norway
- University of Oslo, Oslo, Norway
| | - Gilles Laurent
- Max Planck Institute for Brain Research, Frankfurt, Germany
| | - Nathaniel B. Sawtell
- Department of Neuroscience, Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
| | - Wyeth Bair
- Department of Biological Structure, University of Washington, Seattle, WA, USA
- Washington National Primate Research Center, Seattle, WA, USA
| | - Anitha Pasupathy
- Department of Biological Structure, University of Washington, Seattle, WA, USA
- Washington National Primate Research Center, Seattle, WA, USA
| | | | | | - Liam Paninski
- Department of Neuroscience, Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
| | | | - Christof Koch
- MindScope Program, Allen Institute, Seattle, WA, USA
| | - Shawn R. Olsen
- MindScope Program, Allen Institute, Seattle, WA, USA
- Allen Institute for Neural Dynamics, Seattle, WA, USA
| | - Timothy D. Harris
- Janelia Research Campus, Ashburn, VA, USA
- Biomedical Engineering Department, Johns Hopkins University, Baltimore, MD, USA
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9
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Roese-Miron L, Jones MEH, Ferreira JD, Hsiou AS. Virtual endocasts of Clevosaurus brasiliensis and the tuatara: Rhynchocephalian neuroanatomy and the oldest endocranial record for Lepidosauria. Anat Rec (Hoboken) 2024; 307:1366-1389. [PMID: 36951279 DOI: 10.1002/ar.25212] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 03/02/2023] [Accepted: 03/07/2023] [Indexed: 03/24/2023]
Abstract
Understanding the origins of the vertebrate brain is fundamental for uncovering evolutionary patterns in neuroanatomy. Regarding extinct species, the anatomy of the brain and other soft tissues housed in endocranial spaces can be approximated by casts of these cavities (endocasts). The neuroanatomical knowledge of Rhynchocephalia, a reptilian clade exceptionally diverse in the early Mesozoic, is restricted to the brain of its only living relative, Sphenodon punctatus, and unknown for fossil species. Here, we describe the endocast and the reptilian encephalization quotient (REQ) of the Triassic rhynchocephalian Clevosaurus brasiliensis and compare it with an ontogenetic series of S. punctatus. To better understand the informative potential of endocasts in Rhynchocephalia, we also examine the brain-endocast relationship in S. punctatus. We found that the brain occupies 30% of its cavity, but the latter recovers the general shape and length of the brain. The REQ of C. brasiliensis (0.27) is much lower than S. punctatus (0.84-1.16), with the tuatara being close to the mean for non-avian reptiles. The endocast of S. punctatus is dorsoventrally flexed and becomes more elongated throughout ontogeny. The endocast of C. brasiliensis is mostly unflexed and tubular, possibly representing a more plesiomorphic anatomy in relation to S. punctatus. Given the small size of C. brasiliensis, the main differences may result from allometric and heterochronic phenomena, consistent with suggestions that S. punctatus shows peramorphic anatomy compared to Mesozoic rhynchocephalians. Our results highlight a previously undocumented anatomical diversity among rhynchocephalians and provide a framework for future neuroanatomical comparisons among lepidosaurs.
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Affiliation(s)
- Lívia Roese-Miron
- Programa de Pós-Graduação em Biodiversidade Animal, Universidade Federal de Santa Maria, Santa Maria, Brazil
| | - Marc Emyr Huw Jones
- Science Group: Fossil Reptiles, Amphibians and Birds Section, Natural History Museum, London, UK
- Research Department of Cell and Developmental Biology, University College London, London, UK
- School of Biological Sciences, The University of Adelaide, Adelaide, South Australia, Australia
| | - José Darival Ferreira
- Programa de Pós-Graduação em Biodiversidade Animal, Universidade Federal de Santa Maria, Santa Maria, Brazil
| | - Annie Schmaltz Hsiou
- Departamento de Biologia, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, Brazil
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10
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Storks L, Garcia J, Perez-Martinez CA, Leal M. Habitat complexity influences neuron number in six species of Puerto Rican Anolis. Biol Lett 2024; 20:20230419. [PMID: 38320619 PMCID: PMC10846941 DOI: 10.1098/rsbl.2023.0419] [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: 09/09/2023] [Accepted: 01/15/2024] [Indexed: 02/08/2024] Open
Abstract
Elucidating the selective forces shaping the diversity of vertebrate brains continues to be a major area of inquiry, particularly as it relates to cognition. Historically brain evolution was interpreted through the lens of relative brain size; however, recent evidence has challenged this approach. Investigating neuroanatomy at a finer scale, such as neuron number, can provide new insights into the forces shaping brain evolution in the context of information processing capacity. Ecological factors, such as the complexity of a species' habitat, place demands on cognition that could shape neuroanatomy. In this study, we investigate the relationship between neuron number and habitat complexity in three brain regions across six closely related anole species from Puerto Rico. After controlling for brain mass, we found that the number of neurons increased with habitat complexity across species in the telencephalon and 'rest of the brain,' but not in the cerebellum. Our results demonstrate that habitat complexity has shaped neuroanatomy in the Puerto Rican anole radiation and provide further evidence of the role of habitat complexity in vertebrate brain evolution.
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Affiliation(s)
- Levi Storks
- Division of Biological Sciences, University of Missouri, Columbia, MO, USA
- Department of Biology, University of Detroit Mercy, Detroit, MI, USA
| | - Jessica Garcia
- Division of Biological Sciences, University of Missouri, Columbia, MO, USA
- College of Veterinary Medicine, University of Minnesota, Minneapolis, MN, USA
| | | | - Manuel Leal
- Division of Biological Sciences, University of Missouri, Columbia, MO, USA
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11
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Observing mammalian cerebellum development through an evolutionary lens. Nature 2024:10.1038/d41586-023-03836-3. [PMID: 38200332 DOI: 10.1038/d41586-023-03836-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2024]
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12
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Graïc JM, Corain L, Finos L, Vadori V, Grisan E, Gerussi T, Orekhova K, Centelleghe C, Cozzi B, Peruffo A. Age-related changes in the primary auditory cortex of newborn, adults and aging bottlenose dolphins ( Tursiops truncatus) are located in the upper cortical layers. Front Neuroanat 2024; 17:1330384. [PMID: 38250022 PMCID: PMC10796513 DOI: 10.3389/fnana.2023.1330384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Accepted: 12/06/2023] [Indexed: 01/23/2024] Open
Abstract
Introduction The auditory system of dolphins and whales allows them to dive in dark waters, hunt for prey well below the limit of solar light absorption, and to communicate with their conspecific. These complex behaviors require specific and sufficient functional circuitry in the neocortex, and vicarious learning capacities. Dolphins are also precocious animals that can hold their breath and swim within minutes after birth. However, diving and hunting behaviors are likely not innate and need to be learned. Our hypothesis is that the organization of the auditory cortex of dolphins grows and mature not only in the early phases of life, but also in adults and aging individuals. These changes may be subtle and involve sub-populations of cells specificall linked to some circuits. Methods In the primary auditory cortex of 11 bottlenose dolphins belonging to three age groups (calves, adults, and old animals), neuronal cell shapes were analyzed separately and by cortical layer using custom computer vision and multivariate statistical analysis, to determine potential minute morphological differences across these age groups. Results The results show definite changes in interneurons, characterized by round and ellipsoid shapes predominantly located in upper cortical layers. Notably, neonates interneurons exhibited a pattern of being closer together and smaller, developing into a more dispersed and diverse set of shapes in adulthood. Discussion This trend persisted in older animals, suggesting a continuous development of connections throughout the life of these marine animals. Our findings further support the proposition that thalamic input reach upper layers in cetaceans, at least within a cortical area critical for their survival. Moreover, our results indicate the likelihood of changes in cell populations occurring in adult animals, prompting the need for characterization.
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Affiliation(s)
- Jean-Marie Graïc
- Department of Comparative Biomedicine and Food Science, University of Padova, Legnaro, Italy
| | - Livio Corain
- Department of Management and Engineering, University of Padova, Vicenza, Italy
| | - Livio Finos
- Department of Statistical Sciences, University of Padova, Padua, Italy
| | - Valentina Vadori
- Department of Computer Science and Informatics, London South Bank University, London, United Kingdom
| | - Enrico Grisan
- Department of Computer Science and Informatics, London South Bank University, London, United Kingdom
| | - Tommaso Gerussi
- Department of Comparative Biomedicine and Food Science, University of Padova, Legnaro, Italy
| | - Ksenia Orekhova
- Department of Comparative Biomedicine and Food Science, University of Padova, Legnaro, Italy
| | - Cinzia Centelleghe
- Department of Comparative Biomedicine and Food Science, University of Padova, Legnaro, Italy
| | - Bruno Cozzi
- Department of Comparative Biomedicine and Food Science, University of Padova, Legnaro, Italy
| | - Antonella Peruffo
- Department of Comparative Biomedicine and Food Science, University of Padova, Legnaro, Italy
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13
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Sepp M, Leiss K, Murat F, Okonechnikov K, Joshi P, Leushkin E, Spänig L, Mbengue N, Schneider C, Schmidt J, Trost N, Schauer M, Khaitovich P, Lisgo S, Palkovits M, Giere P, Kutscher LM, Anders S, Cardoso-Moreira M, Sarropoulos I, Pfister SM, Kaessmann H. Cellular development and evolution of the mammalian cerebellum. Nature 2024; 625:788-796. [PMID: 38029793 PMCID: PMC10808058 DOI: 10.1038/s41586-023-06884-x] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Accepted: 11/21/2023] [Indexed: 12/01/2023]
Abstract
The expansion of the neocortex, a hallmark of mammalian evolution1,2, was accompanied by an increase in cerebellar neuron numbers3. However, little is known about the evolution of the cellular programmes underlying the development of the cerebellum in mammals. In this study we generated single-nucleus RNA-sequencing data for around 400,000 cells to trace the development of the cerebellum from early neurogenesis to adulthood in human, mouse and the marsupial opossum. We established a consensus classification of the cellular diversity in the developing mammalian cerebellum and validated it by spatial mapping in the fetal human cerebellum. Our cross-species analyses revealed largely conserved developmental dynamics of cell-type generation, except for Purkinje cells, for which we observed an expansion of early-born subtypes in the human lineage. Global transcriptome profiles, conserved cell-state markers and gene-expression trajectories across neuronal differentiation show that cerebellar cell-type-defining programmes have been overall preserved for at least 160 million years. However, we also identified many orthologous genes that gained or lost expression in cerebellar neural cell types in one of the species or evolved new expression trajectories during neuronal differentiation, indicating widespread gene repurposing at the cell-type level. In sum, our study unveils shared and lineage-specific gene-expression programmes governing the development of cerebellar cells and expands our understanding of mammalian brain evolution.
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Affiliation(s)
- Mari Sepp
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, Heidelberg, Germany.
| | - Kevin Leiss
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, Heidelberg, Germany.
| | - Florent Murat
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, Heidelberg, Germany
- INRAE, LPGP, Rennes, France
| | - Konstantin Okonechnikov
- Hopp-Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Piyush Joshi
- Hopp-Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany
- Developmental Origins of Pediatric Cancer Junior Group, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Evgeny Leushkin
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, Heidelberg, Germany
| | - Lisa Spänig
- Hopp-Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany
- Developmental Origins of Pediatric Cancer Junior Group, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Noe Mbengue
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, Heidelberg, Germany
| | - Céline Schneider
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, Heidelberg, Germany
| | - Julia Schmidt
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, Heidelberg, Germany
| | - Nils Trost
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, Heidelberg, Germany
| | - Maria Schauer
- Museum für Naturkunde Berlin, Leibniz Institute for Evolution and Biodiversity Science, Berlin, Germany
| | - Philipp Khaitovich
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Steven Lisgo
- Biosciences Institute, Newcastle University, Newcastle, UK
| | - Miklós Palkovits
- Human Brain Tissue Bank, Semmelweis University, Budapest, Hungary
| | - Peter Giere
- Museum für Naturkunde Berlin, Leibniz Institute for Evolution and Biodiversity Science, Berlin, Germany
| | - Lena M Kutscher
- Hopp-Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- Developmental Origins of Pediatric Cancer Junior Group, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Simon Anders
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, Heidelberg, Germany
- BioQuant, Heidelberg University, Heidelberg, Germany
| | | | - Ioannis Sarropoulos
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, Heidelberg, Germany.
- Wellcome Sanger Institute, Cambridge, UK.
| | - Stefan M Pfister
- Hopp-Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany.
- Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany.
- Department of Pediatric Hematology and Oncology, Heidelberg University Hospital, Heidelberg, Germany.
- National Center for Tumor Diseases (NCT), Heidelberg, Germany.
| | - Henrik Kaessmann
- Center for Molecular Biology of Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, Heidelberg, Germany.
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Hofman MA. The Fractal Geometry of the Human Brain: An Evolutionary Perspective. ADVANCES IN NEUROBIOLOGY 2024; 36:241-258. [PMID: 38468036 DOI: 10.1007/978-3-031-47606-8_12] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/13/2024]
Abstract
The evolution of the brain in mammals is characterized by changes in size, architecture, and internal organization. Consequently, the geometry of the brain, and especially the size and shape of the cerebral cortex, has changed notably during evolution. Comparative studies of the cerebral cortex suggest that there are general architectural principles governing its growth and evolutionary development. In this chapter, some of the design principles and operational modes that underlie the fractal geometry and information processing capacity of the cerebral cortex in primates, including humans, will be explored. It is shown that the development of the cortex coordinates folding with connectivity in a way that produces smaller and faster brains.
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Affiliation(s)
- Michel A Hofman
- Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands.
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15
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Ferreira VHB, Lansade L, Calandreau L, Cunha F, Jensen P. Are domesticated animals dumber than their wild relatives? A comprehensive review on the domestication effects on animal cognitive performance. Neurosci Biobehav Rev 2023; 154:105407. [PMID: 37769929 DOI: 10.1016/j.neubiorev.2023.105407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 09/21/2023] [Accepted: 09/22/2023] [Indexed: 10/03/2023]
Abstract
Animal domestication leads to diverse behavioral, physiological, and neurocognitive changes in domesticated species compared to their wild relatives. However, the widely held belief that domesticated species are inherently less "intelligent" (i.e., have lower cognitive performance) than their wild counterparts requires further investigation. To investigate potential cognitive disparities, we undertook a thorough review of 88 studies comparing the cognitive performance of domesticated and wild animals. Approximately 30% of these studies showed superior cognitive abilities in wild animals, while another 30% highlighted superior cognitive abilities in domesticated animals. The remaining 40% of studies found similar cognitive performance between the two groups. Therefore, the question regarding the presumed intelligence of wild animals and the diminished cognitive ability of domesticated animals remains unresolved. We discuss important factors/limitations for interpreting past and future research, including environmental influences, diverse objectives of domestication (such as breed development), developmental windows, and methodological issues impacting cognitive comparisons. Rather than perceiving these limitations as constraints, future researchers should embrace them as opportunities to expand our understanding of the complex relationship between domestication and animal cognition.
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Affiliation(s)
- Vitor Hugo Bessa Ferreira
- IFM Biology, AVIAN Behavioural Genomics and Physiology group, Linköping University, 581 83 Linköping, Sweden; INRAE, CNRS, IFCE, Université de Tours, Centre Val de Loire UMR Physiologie de la Reproduction et des Comportements, 37380 Nouzilly, France.
| | - Léa Lansade
- INRAE, CNRS, IFCE, Université de Tours, Centre Val de Loire UMR Physiologie de la Reproduction et des Comportements, 37380 Nouzilly, France
| | - Ludovic Calandreau
- INRAE, CNRS, IFCE, Université de Tours, Centre Val de Loire UMR Physiologie de la Reproduction et des Comportements, 37380 Nouzilly, France
| | - Felipe Cunha
- IFM Biology, AVIAN Behavioural Genomics and Physiology group, Linköping University, 581 83 Linköping, Sweden
| | - Per Jensen
- IFM Biology, AVIAN Behavioural Genomics and Physiology group, Linköping University, 581 83 Linköping, Sweden.
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16
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Watanabe A, Marshall SS, Gignac PM. Dumbbell-shaped brains of Polish crested chickens as a model system for the evolution of novel brain morphologies. J Anat 2023; 243:421-430. [PMID: 37165612 PMCID: PMC10439378 DOI: 10.1111/joa.13883] [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: 10/30/2022] [Revised: 03/28/2023] [Accepted: 04/27/2023] [Indexed: 05/12/2023] Open
Abstract
The evolutionary history of vertebrates is replete with emergence of novel brain morphologies, including the origin of the human brain. Existing model organisms and toolkits for investigating drivers of neuroanatomical innovations have largely proceeded on mammals. As such, a compelling non-mammalian model system would facilitate our understanding of how unique brain morphologies evolve across vertebrates. Here, we present the domestic chicken breed, white crested Polish chickens, as an avian model for investigating how novel brain morphologies originate. Most notably, these crested chickens exhibit cerebral herniation from anterodorsal displacement of the telencephalon, which results in a prominent protuberance on the dorsal aspect of the skull. We use a high-density geometric morphometric approach on cephalic endocasts to characterize their brain morphology. Compared with standard white Leghorn chickens (WLCs) and modern avian diversity, the results demonstrate that crested chickens possess a highly variable and unique overall brain configuration. Proportional sizes of neuroanatomical regions are within the observed range of extant birds sampled in this study, but Polish chickens differ from WLCs in possessing a relatively larger cerebrum and smaller cerebellum and medulla. Given their accessibility, phylogenetic proximity, and unique neuroanatomy, we propose that crested breeds, combined with standard chickens, form a promising comparative system for investigating the emergence of novel brain morphologies.
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Affiliation(s)
- Akinobu Watanabe
- Department of AnatomyNew York Institute of Technology College of Osteopathic MedicineOld WestburyNew YorkUSA
- Division of PaleontologyAmerican Museum of Natural HistoryNew YorkNew YorkUSA
- Department of Life SciencesNatural History MuseumLondonUK
| | - Sylvia S. Marshall
- Department of AnatomyNew York Institute of Technology College of Osteopathic MedicineOld WestburyNew YorkUSA
| | - Paul M. Gignac
- Division of PaleontologyAmerican Museum of Natural HistoryNew YorkNew YorkUSA
- Department of Cellular and Molecular MedicineUniversity of Arizona College of MedicineTucsonArizonaUSA
- MicroCT Imaging Consortium for Research and OutreachUniversity of ArkansasFayettevilleArkansasUSA
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17
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Kozol RA, Conith AJ, Yuiska A, Cree-Newman A, Tolentino B, Benesh K, Paz A, Lloyd E, Kowalko JE, Keene AC, Albertson C, Duboue ER. A brain-wide analysis maps structural evolution to distinct anatomical module. eLife 2023; 12:e80777. [PMID: 37498318 PMCID: PMC10435234 DOI: 10.7554/elife.80777] [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: 06/03/2022] [Accepted: 07/26/2023] [Indexed: 07/28/2023] Open
Abstract
The vertebrate brain is highly conserved topologically, but less is known about neuroanatomical variation between individual brain regions. Neuroanatomical variation at the regional level is hypothesized to provide functional expansion, building upon ancestral anatomy needed for basic functions. Classically, animal models used to study evolution have lacked tools for detailed anatomical analysis that are widely used in zebrafish and mice, presenting a barrier to studying brain evolution at fine scales. In this study, we sought to investigate the evolution of brain anatomy using a single species of fish consisting of divergent surface and cave morphs, that permits functional genetic testing of regional volume and shape across the entire brain. We generated a high-resolution brain atlas for the blind Mexican cavefish Astyanax mexicanus and coupled the atlas with automated computational tools to directly assess variability in brain region shape and volume across all populations. We measured the volume and shape of every grossly defined neuroanatomical region of the brain and assessed correlations between anatomical regions in surface fish, cavefish, and surface × cave F2 hybrids, whose phenotypes span the range of surface to cave. We find that dorsal regions of the brain are contracted, while ventral regions have expanded, with F2 hybrid data providing support for developmental constraint along the dorsal-ventral axis. Furthermore, these dorsal-ventral relationships in anatomical variation show similar patterns for both volume and shape, suggesting that the anatomical evolution captured by these two parameters could be driven by similar developmental mechanisms. Together, these data demonstrate that A. mexicanus is a powerful system for functionally determining basic principles of brain evolution and will permit testing how genes influence early patterning events to drive brain-wide anatomical evolution.
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Affiliation(s)
- Robert A Kozol
- Jupiter Life Science Initiative, Florida Atlantic UniversityJupiterUnited States
| | - Andrew J Conith
- Department of Biology, University of Massachusetts AmherstAmherstUnited States
| | - Anders Yuiska
- Jupiter Life Science Initiative, Florida Atlantic UniversityJupiterUnited States
| | - Alexia Cree-Newman
- Jupiter Life Science Initiative, Florida Atlantic UniversityJupiterUnited States
| | - Bernadeth Tolentino
- Jupiter Life Science Initiative, Florida Atlantic UniversityJupiterUnited States
| | - Kasey Benesh
- Jupiter Life Science Initiative, Florida Atlantic UniversityJupiterUnited States
| | - Alexandra Paz
- Jupiter Life Science Initiative, Florida Atlantic UniversityJupiterUnited States
| | - Evan Lloyd
- Department of Biology, Texas A&M UniversityCollege StationUnited States
| | - Johanna E Kowalko
- Department of Biological Sciences, Lehigh UniversityBethlehemUnited States
| | - Alex C Keene
- Department of Biology, Texas A&M UniversityCollege StationUnited States
| | - Craig Albertson
- Department of Biology, University of Massachusetts AmherstAmherstUnited States
| | - Erik R Duboue
- Jupiter Life Science Initiative, Florida Atlantic UniversityJupiterUnited States
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18
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Schwartz E, Nenning KH, Heuer K, Jeffery N, Bertrand OC, Toro R, Kasprian G, Prayer D, Langs G. Evolution of cortical geometry and its link to function, behaviour and ecology. Nat Commun 2023; 14:2252. [PMID: 37080952 PMCID: PMC10119184 DOI: 10.1038/s41467-023-37574-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 03/22/2023] [Indexed: 04/22/2023] Open
Abstract
Studies in comparative neuroanatomy and of the fossil record demonstrate the influence of socio-ecological niches on the morphology of the cerebral cortex, but have led to oftentimes conflicting theories about its evolution. Here, we study the relationship between the shape of the cerebral cortex and the topography of its function. We establish a joint geometric representation of the cerebral cortices of ninety species of extant Euarchontoglires, including commonly used experimental model organisms. We show that variability in surface geometry relates to species' ecology and behaviour, independent of overall brain size. Notably, ancestral shape reconstruction of the cortical surface and its change during evolution enables us to trace the evolutionary history of localised cortical expansions, modal segregation of brain function, and their association to behaviour and cognition. We find that individual cortical regions follow different sequences of area increase during evolutionary adaptations to dynamic socio-ecological niches. Anatomical correlates of this sequence of events are still observable in extant species, and relate to their current behaviour and ecology. We decompose the deep evolutionary history of the shape of the human cortical surface into spatially and temporally conscribed components with highly interpretable functional associations, highlighting the importance of considering the evolutionary history of cortical regions when studying their anatomy and function.
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Affiliation(s)
- Ernst Schwartz
- Department of Biomedical Imaging and Image-guided Therapy, Computational Imaging Research Lab, Medical University of Vienna, Vienna, Austria
| | - Karl-Heinz Nenning
- Department of Biomedical Imaging and Image-guided Therapy, Computational Imaging Research Lab, Medical University of Vienna, Vienna, Austria
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY, USA
| | - Katja Heuer
- Institut Pasteur, Université Paris Cité, Unité de Neuroanatomie Appliquée et Théorique, F-75015, Paris, France
| | - Nathan Jeffery
- Institute of Life Course & Medical Sciences, University of Liverpool, Liverpool, England
| | - Ornella C Bertrand
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona Edifici ICTA-ICP, c/ Columnes s/n, Campus de la UAB, 08193 Cerdanyola del Vallès., Barcelona, Spain
- School of GeoSciences, University of Edinburgh, Grant Institute, Edinburgh, Scotland, EH9 3FE, United Kingdom
| | - Roberto Toro
- Institut Pasteur, Université Paris Cité, Unité de Neuroanatomie Appliquée et Théorique, F-75015, Paris, France
| | - Gregor Kasprian
- Department of Biomedical Imaging and Image-guided Therapy, Computational Imaging Research Lab, Medical University of Vienna, Vienna, Austria
| | - Daniela Prayer
- Department of Biomedical Imaging and Image-guided Therapy, Computational Imaging Research Lab, Medical University of Vienna, Vienna, Austria
| | - Georg Langs
- Department of Biomedical Imaging and Image-guided Therapy, Computational Imaging Research Lab, Medical University of Vienna, Vienna, Austria.
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, USA.
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19
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Herculano-Houzel S. Theropod dinosaurs had primate-like numbers of telencephalic neurons. J Comp Neurol 2023; 531:962-974. [PMID: 36603059 DOI: 10.1002/cne.25453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 12/05/2022] [Accepted: 12/15/2022] [Indexed: 01/07/2023]
Abstract
Understanding the neuronal composition of the brains of dinosaurs and other fossil amniotes would offer fundamental insight into their behavioral and cognitive capabilities, but brain tissue is only rarely fossilized. However, when the bony brain case is preserved, the volume and therefore mass of the brain can be estimated with computer tomography; and if the scaling relationship between brain mass and numbers of neurons for the clade is known, that relationship can be applied to estimate the neuronal composition of the brain. Using a recently published database of numbers of neurons in the telencephalon of extant sauropsids (birds, squamates, and testudines), here I show that the neuronal scaling rules that apply to these animals can be used to infer the numbers of neurons that composed the telencephalon of dinosaur, pterosaur, and other fossil sauropsid species. The key to inferring numbers of telencephalic neurons in these species is first using the relationship between their estimated brain and body mass to determine whether bird-like (endothermic) or squamate-like (ectothermic) rules apply to each fossil sauropsid species. This procedure shows that the notion of "mesothermy" in dinosaurs is an artifact due to the mixing of animals with bird-like and squamate-like scaling, and indicates that theropods such as Tyrannosaurus and Allosaurus were endotherms with baboon- and monkey-like numbers of telencephalic neurons, respectively, which would make these animals not only giant but also long-lived and endowed with flexible cognition, and thus even more magnificent predators than previously thought.
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Affiliation(s)
- Suzana Herculano-Houzel
- Department of Psychology, Vanderbilt University, Nashville, Tennessee, USA.,Department of Biological Sciences, Vanderbilt University, Nashville, Tennessee, USA.,Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee, USA
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20
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Renner J, Rasia-Filho AA. Morphological Features of Human Dendritic Spines. ADVANCES IN NEUROBIOLOGY 2023; 34:367-496. [PMID: 37962801 DOI: 10.1007/978-3-031-36159-3_9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Dendritic spine features in human neurons follow the up-to-date knowledge presented in the previous chapters of this book. Human dendrites are notable for their heterogeneity in branching patterns and spatial distribution. These data relate to circuits and specialized functions. Spines enhance neuronal connectivity, modulate and integrate synaptic inputs, and provide additional plastic functions to microcircuits and large-scale networks. Spines present a continuum of shapes and sizes, whose number and distribution along the dendritic length are diverse in neurons and different areas. Indeed, human neurons vary from aspiny or "relatively aspiny" cells to neurons covered with a high density of intermingled pleomorphic spines on very long dendrites. In this chapter, we discuss the phylogenetic and ontogenetic development of human spines and describe the heterogeneous features of human spiny neurons along the spinal cord, brainstem, cerebellum, thalamus, basal ganglia, amygdala, hippocampal regions, and neocortical areas. Three-dimensional reconstructions of Golgi-impregnated dendritic spines and data from fluorescence microscopy are reviewed with ultrastructural findings to address the complex possibilities for synaptic processing and integration in humans. Pathological changes are also presented, for example, in Alzheimer's disease and schizophrenia. Basic morphological data can be linked to current techniques, and perspectives in this research field include the characterization of spines in human neurons with specific transcriptome features, molecular classification of cellular diversity, and electrophysiological identification of coexisting subpopulations of cells. These data would enlighten how cellular attributes determine neuron type-specific connectivity and brain wiring for our diverse aptitudes and behavior.
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Affiliation(s)
- Josué Renner
- Department of Basic Sciences/Physiology and Graduate Program in Biosciences, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, RS, Brazil
| | - Alberto A Rasia-Filho
- Department of Basic Sciences/Physiology and Graduate Program in Biosciences, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, RS, Brazil
- Graduate Program in Neuroscience, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
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21
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Cunha F, Gutiérrez-Ibáñez C, Brinkman B, Wylie DR, Iwaniuk AN. The relative sizes of nuclei in the oculomotor complex vary by order and behaviour in birds. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 2022; 209:341-360. [PMID: 36522507 DOI: 10.1007/s00359-022-01598-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 10/26/2022] [Accepted: 11/25/2022] [Indexed: 12/23/2022]
Abstract
Eye movements are a critical component of visually guided behaviours, allowing organisms to scan the environment and bring stimuli of interest to regions of acuity in the retina. Although the control and modulation of eye movements by cranial nerve nuclei are highly conserved across vertebrates, species variation in visually guided behaviour and eye morphology could lead to variation in the size of oculomotor nuclei. Here, we test for differences in the size and neuron numbers of the oculomotor nuclei among birds that vary in behaviour and eye morphology. Using unbiased stereology, we measured the volumes and numbers of neurons of the oculomotor (nIII), trochlear (nIV), abducens (nVI), and Edinger-Westphal (EW) nuclei across 71 bird species and analysed these with phylogeny-informed statistics. Owls had relatively smaller nIII, nIV, nVI and EW nuclei than other birds, which reflects their limited degrees of eye movements. In contrast, nVI was relatively larger in falcons and hawks, likely reflecting how these predatory species must shift focus between the central and temporal foveae during foraging and prey capture. Unexpectedly, songbirds had an enlarged EW and relatively more nVI neurons, which might reflect accommodation and horizontal eye movements. Finally, the one merganser we measured also has an enlarged EW, which is associated with the high accommodative power needed for pursuit diving. Overall, these differences reflect species and clade level variation in behaviour, but more data are needed on eye movements in birds across species to better understand the relationships among behaviour, retinal anatomy, and brain anatomy.
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Affiliation(s)
- Felipe Cunha
- Department of Neuroscience, University of Lethbridge, 4401 University Dr W, Lethbridge, AB, T1K 3M4, Canada
| | | | - Benjamin Brinkman
- Department of Neuroscience, University of Lethbridge, 4401 University Dr W, Lethbridge, AB, T1K 3M4, Canada
| | - Douglas R Wylie
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada
| | - Andrew N Iwaniuk
- Department of Neuroscience, University of Lethbridge, 4401 University Dr W, Lethbridge, AB, T1K 3M4, Canada.
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22
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Cunha F, Stingo-Hirmas D, Cardoso RF, Wright D, Henriksen R. Neuronal and non-neuronal scaling across brain regions within an intercross of domestic and wild chickens. Front Neuroanat 2022; 16:1048261. [PMID: 36506870 PMCID: PMC9732670 DOI: 10.3389/fnana.2022.1048261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 11/11/2022] [Indexed: 11/26/2022] Open
Abstract
The allometric scaling of the brain size and neuron number across species has been extensively studied in recent years. With the exception of primates, parrots, and songbirds, larger brains have more neurons but relatively lower neuronal densities than smaller brains. Conversely, when considering within-population variability, it has been shown that mice with larger brains do not necessarily have more neurons but rather more neurons in the brain reflect higher neuronal density. To what extent this intraspecific allometric scaling pattern of the brain applies to individuals from other species remains to be explored. Here, we investigate the allometric relationships among the sizes of the body, brain, telencephalon, cerebellum, and optic tectum, and the numbers of neurons and non-neuronal cells of the telencephalon, cerebellum, and optic tectum across 66 individuals originated from an intercross between wild and domestic chickens. Our intercross of chickens generates a population with high variation in brain size, making it an excellent model to determine the allometric scaling of the brain within population. Our results show that larger chickens have larger brains with moderately more neurons and non-neuronal cells. Yet, absolute number of neurons and non-neuronal cells correlated strongly and positively with the density of neurons and non-neuronal cells, respectively. As previously shown in mice, this scaling pattern is in stark contrast with what has been found across different species. Our findings suggest that neuronal scaling rules across species are not a simple extension of the neuronal scaling rules that apply within a species, with important implications for the evolutionary developmental origins of brain diversity.
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23
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von Eugen K, Endepols H, Drzezga A, Neumaier B, Güntürkün O, Backes H, Ströckens F. Avian neurons consume three times less glucose than mammalian neurons. Curr Biol 2022; 32:4306-4313.e4. [PMID: 36084646 DOI: 10.1016/j.cub.2022.07.070] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 04/11/2022] [Accepted: 07/26/2022] [Indexed: 12/14/2022]
Abstract
Brains are among the most energetically costly tissues in the mammalian body.1 This is predominantly caused by expensive neurons with high glucose demands.2 Across mammals, the neuronal energy budget appears to be fixed, possibly posing an evolutionary constraint on brain growth.3-6 Compared to similarly sized mammals, birds have higher numbers of neurons, and this advantage conceivably contributes to their cognitive prowess.7 We set out to determine the neuronal energy budget of birds to elucidate how they can metabolically support such high numbers of neurons. We estimated glucose metabolism using positron emission tomography (PET) and 2-[18F]fluoro-2-deoxyglucose ([18F]FDG) as the radiotracer in awake and anesthetized pigeons. Combined with kinetic modeling, this is the gold standard to quantify cerebral metabolic rate of glucose consumption (CMRglc).8 We found that neural tissue in the pigeon consumes 27.29 ± 1.57 μmol glucose per 100 g per min in an awake state, which translates into a surprisingly low neuronal energy budget of 1.86 × 10-9 ± 0.2 × 10-9 μmol glucose per neuron per minute. This is approximately 3 times lower than the rate in the average mammalian neuron.3 The remarkably low neuronal energy budget explains how pigeons, and possibly other avian species, can support such high numbers of neurons without associated metabolic costs or compromising neuronal signaling. The advantage in neuronal processing of information at a higher efficiency possibly emerged during the distinct evolution of the avian brain.
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Affiliation(s)
- Kaya von Eugen
- Department of Biopsychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, Bochum, Germany
| | - Heike Endepols
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital of Cologne, Cologne, Germany; Institute of Radiochemistry and Experimental Molecular Imaging, Faculty of Medicine and University Hospital of Cologne, Cologne, Germany; Institute of Neuroscience and Medicine, INM-5: Nuclear Chemistry, Forschungszentrum Jülich GmbH, Jülich, Germany
| | - Alexander Drzezga
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital of Cologne, Cologne, Germany; Institute of Neuroscience and Medicine, INM-2: Molecular Organization of the Brain, Forschungszentrum Jülich GmbH, Jülich, Germany; German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany
| | - Bernd Neumaier
- Institute of Radiochemistry and Experimental Molecular Imaging, Faculty of Medicine and University Hospital of Cologne, Cologne, Germany; Institute of Neuroscience and Medicine, INM-5: Nuclear Chemistry, Forschungszentrum Jülich GmbH, Jülich, Germany
| | - Onur Güntürkün
- Department of Biopsychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, Bochum, Germany
| | - Heiko Backes
- Max Planck Institute for Metabolism Research, Multimodal Imaging Group, Cologne, Germany
| | - Felix Ströckens
- Department of Biopsychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, Bochum, Germany; Cécile and Oskar Vogt Institute of Brain Research, University Hospital Düsseldorf, Heinrich-Heine University, Düsseldorf, Germany.
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24
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The impact of environmental factors on the evolution of brain size in carnivorans. Commun Biol 2022; 5:998. [PMID: 36130990 PMCID: PMC9492690 DOI: 10.1038/s42003-022-03748-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 07/20/2022] [Indexed: 11/28/2022] Open
Abstract
The reasons why some animals have developed larger brains has long been a subject of debate. Yet, it remains unclear which selective pressures may favour the encephalization and how it may act during evolution at different taxonomic scales. Here we studied the patterns and tempo of brain evolution within the order Carnivora and present large-scale comparative analysis of the effect of ecological, environmental, social, and physiological variables on relative brain size in a sample of 174 extant carnivoran species. We found a complex pattern of brain size change between carnivoran families with differences in both the rate and diversity of encephalization. Our findings suggest that during carnivorans’ evolution, a trade-off have occurred between the cognitive advantages of acquiring a relatively large brain allowing to adapt to specific environments, and the metabolic costs of the brain which may constitute a disadvantage when facing the need to colonize new environments. The brain size of carnivores has evolved to balance a trade-off between increased cognitive function and increased metabolic cost.
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25
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Abstract
The reasons why some animals have developed larger brains has long been a subject of debate. Yet, it remains unclear which selective pressures may favour the encephalization and how it may act during evolution at different taxonomic scales. Here we studied the patterns and tempo of brain evolution within the order Carnivora and present large-scale comparative analysis of the effect of ecological, environmental, social, and physiological variables on relative brain size in a sample of 174 extant carnivoran species. We found a complex pattern of brain size change between carnivoran families with differences in both the rate and diversity of encephalization. Our findings suggest that during carnivorans' evolution, a trade-off have occurred between the cognitive advantages of acquiring a relatively large brain allowing to adapt to specific environments, and the metabolic costs of the brain which may constitute a disadvantage when facing the need to colonize new environments.
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26
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Ventura-Antunes AL, Herculano-Houzel S. Energy supply per neuron is constrained by capillary density in the mouse brain. Front Integr Neurosci 2022; 16:760887. [PMID: 36105258 PMCID: PMC9465999 DOI: 10.3389/fnint.2022.760887] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 07/28/2022] [Indexed: 11/18/2022] Open
Abstract
Neuronal densities vary enormously across sites within a brain. Does the density of the capillary bed vary accompanying the presumably larger energy requirement of sites with more neurons, or with larger neurons, or is energy supply constrained by a mostly homogeneous capillary bed? Here we find evidence for the latter, with a capillary bed that represents typically between 0.7 and 1.5% of the volume of the parenchyma across various sites in the mouse brain, whereas neuronal densities vary by at least 100-fold. As a result, the ratio of capillary cells per neuron decreases uniformly with increasing neuronal density and therefore with smaller average neuronal size across sites. Thus, given the relatively constant capillary density compared to neuronal density in the brain, blood and energy availability per neuron is presumably dependent on how many neurons compete for the limited supply provided by a mostly homogeneous capillary bed. Additionally, we find that local capillary density is not correlated with local synapse densities, although there is a small but significant correlation between lower neuronal density (and therefore larger neuronal size) and more synapses per neuron within the restricted range of 6,500–9,500 across cortical sites. Further, local variations in the glial/neuron ratio are not correlated with local variations in the number of synapses per neuron or local synaptic densities. These findings suggest that it is not that larger neurons, neurons with more synapses, or even sites with more synapses demand more energy, but simply that larger neurons (in low density sites) have more energy available per cell and for the totality of its synapses than smaller neurons (in high density sites) due to competition for limited resources supplied by a capillary bed of fairly homogeneous density throughout the brain.
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Affiliation(s)
- aLissa Ventura-Antunes
- Instituto de Ciências Biomédicas, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
- Department of Psychology, Vanderbilt University, Nashville, TN, United States
- Department of Neurology, Vanderbilt Medical Center, Nashville, TN, United States
| | - Suzana Herculano-Houzel
- Department of Psychology, Vanderbilt University, Nashville, TN, United States
- Department of Biological Sciences, Vanderbilt University, Nashville, TN, United States
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, United States
- *Correspondence: Suzana Herculano-Houzel,
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27
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Neuron numbers link innovativeness with both absolute and relative brain size in birds. Nat Ecol Evol 2022; 6:1381-1389. [PMID: 35817825 DOI: 10.1038/s41559-022-01815-x] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Accepted: 05/19/2022] [Indexed: 12/31/2022]
Abstract
A longstanding issue in biology is whether the intelligence of animals can be predicted by absolute or relative brain size. However, progress has been hampered by an insufficient understanding of how neuron numbers shape internal brain organization and cognitive performance. On the basis of estimations of neuron numbers for 111 bird species, we show here that the number of neurons in the pallial telencephalon is positively associated with a major expression of intelligence: innovation propensity. The number of pallial neurons, in turn, is greater in brains that are larger in both absolute and relative terms and positively covaries with longer post-hatching development periods. Thus, our analyses show that neuron numbers link cognitive performance to both absolute and relative brain size through developmental adjustments. These findings help unify neuro-anatomical measures at multiple levels, reconciling contradictory views over the biological significance of brain expansion. The results also highlight the value of a life history perspective to advance our understanding of the evolutionary bases of the connections between brain and cognition.
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28
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Adalbert R, Cahalan S, Hopkins EL, Almuhanna A, Loreto A, Pór E, Körmöczy L, Perkins J, Coleman MP, Piercy RJ. Cultured dissociated primary dorsal root ganglion neurons from adult horses enable study of axonal transport. J Anat 2022; 241:1211-1218. [PMID: 35728923 PMCID: PMC9558156 DOI: 10.1111/joa.13719] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 06/12/2022] [Accepted: 06/13/2022] [Indexed: 11/29/2022] Open
Abstract
Neurological disorders are prevalent in horses, but their study is challenging due to anatomic constraints and the large body size; very few host‐specific in vitro models have been established to study these types of diseases, particularly from adult donor tissue. Here we report the generation of primary neuronal dorsal root ganglia (DRG) cultures from adult horses: the mixed, dissociated cultures, containing neurons and glial cells, remained viable for at least 90 days. Similar to DRG neurons in vivo, cultured neurons varied in size, and they developed long neurites. The mitochondrial movement was detected in cultured cells and was significantly slower in glial cells compared to DRG‐derived neurons. In addition, mitochondria were more elongated in glial cells than those in neurons. Our culture model will be a useful tool to study the contribution of axonal transport defects to specific neurodegenerative diseases in horses as well as comparative studies aimed at evaluating species‐specific differences in axonal transport and survival.
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Affiliation(s)
- Robert Adalbert
- Comparative Neuromuscular Diseases Laboratory, Department of Clinical Science and Services, Royal Veterinary College, London, UK.,Department of Anatomy, Histology, and Embryology, Faculty of Medicine, University of Szeged, Szeged, Hungary
| | - Stephen Cahalan
- Comparative Neuromuscular Diseases Laboratory, Department of Clinical Science and Services, Royal Veterinary College, London, UK
| | - Eleanor L Hopkins
- John van Geest Centre for Brain Repair, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Abdulaziz Almuhanna
- Comparative Neuromuscular Diseases Laboratory, Department of Clinical Science and Services, Royal Veterinary College, London, UK
| | - Andrea Loreto
- John van Geest Centre for Brain Repair, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.,Andrea Loreto, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK
| | - Erzsébet Pór
- Department of Anatomy, Histology, and Embryology, Faculty of Medicine, University of Szeged, Szeged, Hungary
| | - Laura Körmöczy
- Department of Anatomy, Histology, and Embryology, Faculty of Medicine, University of Szeged, Szeged, Hungary
| | - Justin Perkins
- Comparative Neuromuscular Diseases Laboratory, Department of Clinical Science and Services, Royal Veterinary College, London, UK
| | - Michael P Coleman
- John van Geest Centre for Brain Repair, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Richard J Piercy
- Comparative Neuromuscular Diseases Laboratory, Department of Clinical Science and Services, Royal Veterinary College, London, UK
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29
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Garin CM, Garin M, Silenzi L, Jaffe R, Constantinidis C. Multilevel atlas comparisons reveal divergent evolution of the primate brain. Proc Natl Acad Sci U S A 2022; 119:e2202491119. [PMID: 35700361 PMCID: PMC9231627 DOI: 10.1073/pnas.2202491119] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2022] [Accepted: 04/25/2022] [Indexed: 01/08/2023] Open
Abstract
Whether the size of the prefrontal cortex (PFC) in humans is disproportionate when compared to other species is a persistent debate in evolutionary neuroscience. This question has left the study of over/under-expansion in other structures relatively unexplored. We therefore sought to address this gap by adapting anatomical areas from the digital atlases of 18 mammalian species, to create a common interspecies classification. Our approach used data-driven analysis based on phylogenetic generalized least squares to evaluate anatomical expansion covering the whole brain. Our main finding suggests a divergence in primate evolution, orienting the stereotypical mammalian cerebral proportion toward a frontal and parietal lobe expansion in catarrhini (primate parvorder comprising old world monkeys, apes, and humans). Cerebral lobe volumes slopes plotted for catarrhini species were ranked as parietal∼frontal > temporal > occipital, contrasting with the ranking of other mammalian species (occipital > temporal > frontal∼parietal). Frontal and parietal slopes were statistically different in catarrhini when compared to other species through bootstrap analysis. Within the catarrhini's frontal lobe, the prefrontal cortex was the principal driver of frontal expansion. Across all species, expansion of the frontal lobe appeared to be systematically linked to the parietal lobe. Our findings suggest that the human frontal and parietal lobes are not disproportionately enlarged when compared to other catarrhini. Nevertheless, humans remain unique in carrying the most relatively enlarged frontal and parietal lobes in an infraorder exhibiting a disproportionate expansion of these areas.
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Affiliation(s)
- Clément M. Garin
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235
| | - Marie Garin
- Département de Mathématiques, Université Paris-Saclay, ENS Paris-Saclay, CNRS, Centre Borelli, Gif-sur-Yvette, F-91190 France
| | - Leonardo Silenzi
- Department of Neurobiology and Anatomy, Wake Forest School of Medicine, Winston Salem, NC 27157
| | - Rye Jaffe
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235
- Department of Neurobiology and Anatomy, Wake Forest School of Medicine, Winston Salem, NC 27157
| | - Christos Constantinidis
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235
- Program in Neuroscience, Vanderbilt University, Nashville, TN 37235
- Department of Ophthalmology and Visual Sciences, Vanderbilt University Medical Center, Nashville, TN 37232
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30
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Schumacher EL, Carlson BA. Convergent mosaic brain evolution is associated with the evolution of novel electrosensory systems in teleost fishes. eLife 2022; 11:74159. [PMID: 35713403 PMCID: PMC9333993 DOI: 10.7554/elife.74159] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Accepted: 06/16/2022] [Indexed: 11/16/2022] Open
Abstract
Brain region size generally scales allometrically with brain size, but mosaic shifts in brain region size independent of brain size have been found in several lineages and may be related to the evolution of behavioral novelty. African weakly electric fishes (Mormyroidea) evolved a mosaically enlarged cerebellum and hindbrain, yet the relationship to their behaviorally novel electrosensory system remains unclear. We addressed this by studying South American weakly electric fishes (Gymnotiformes) and weakly electric catfishes (Synodontis spp.), which evolved varying aspects of electrosensory systems, independent of mormyroids. If the mormyroid mosaic increases are related to evolving an electrosensory system, we should find similar mosaic shifts in gymnotiforms and Synodontis. Using micro-computed tomography scans, we quantified brain region scaling for multiple electrogenic, electroreceptive, and non-electrosensing species. We found mosaic increases in cerebellum in all three electrogenic lineages relative to non-electric lineages and mosaic increases in torus semicircularis and hindbrain associated with the evolution of electrogenesis and electroreceptor type. These results show that evolving novel electrosensory systems is repeatedly and independently associated with changes in the sizes of individual major brain regions independent of brain size, suggesting that selection can impact structural brain composition to favor specific regions involved in novel behaviors. Larger animals tend to have larger brains and smaller animals tend to have smaller ones. However, some species do not fit the pattern that would be expected based on their body size. This variation between species can also apply to individual brain regions. This may be due to evolutionary forces shaping the brain when favouring particular behaviours. However, it is difficult to directly link changes in species behaviour and variations in brain structure. One way to understand the impact of evolutionary adaptations is to study species that have developed new behaviours and compare them to related ones that lack such a behaviour. An opportunity to do this lies in the ability of several species of fish to produce and sense electric fields in water. While this system is not found in most fish, it has evolved multiple times independently in distantly-related lineages. Schumacher and Carlson examined whether differences in the size of brains and individual regions between species were associated with the evolution of electric field generation and sensing. Micro-computed tomography, or μCT, scans of the brains of multiple fish species revealed that the species that can produce electricity – also known as ‘electrogenic’ species’ – have more similar brain structures to each other than to their close relatives that lack this ability. The brain regions involved in producing and detecting electrical charges were larger in these electrogenic fish. This similarity was apparent despite variations in how total brain size has evolved with body size across species. These results demonstrate how evolutionary forces acting on particular behaviours can lead to predictable changes in brain structure. Understanding how and why brains evolve will allow researchers to better predict how species’ brains and behaviours may adapt as human activities alter their environments.
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Affiliation(s)
- Erika L Schumacher
- Department of Biology, Washington University in St. Louis, St. Louis, United States
| | - Bruce A Carlson
- Department of Biology, Washington University in St. Louis, St. Louis, United States
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White Matter, Behavioral Neurology, and the Influence of Corticocentrism. Cogn Behav Neurol 2022; 35:147-152. [PMID: 35486535 DOI: 10.1097/wnn.0000000000000302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Accepted: 11/16/2021] [Indexed: 11/26/2022]
Abstract
White matter in the human brain occupies roughly the same volume as gray matter but has received far less attention in behavioral neurology and related disciplines. In particular, the cerebral cortex has long dominated thinking about the organization of brain-behavior relationships. As a result, subcortical structures, including deep gray matter and, most notably, white matter, have been accorded relatively little neuroscientific study compared with the extensive work devoted to the cerebral cortex. The influence of corticocentrism can be explained by several factors, including historical precedent in neurology strongly emphasizing the importance of the cortex, a preponderance of investigative methods that selectively target this structure, and a misinterpretation of comparative neuroanatomic data gathered from normal brains. This paper will describe the background of the corticocentric bias and emphasize that white matter merits its own place within the study of the higher functions. Although corticocentrism continues to exert a powerful impact on behavioral neurology, considerable progress is being made in the study of white matter-a development that promises to expand our knowledge of the normal brain and lead to an improved understanding of how it mediates behavior. In turn, a range of vexing neurologic and psychiatric disorders may become better illuminated by considering pathology within, or dysfunction of, white matter tracts. A complete appreciation of brain-behavior relationships requires an understanding not only of the outermost layer of the cerebral hemispheres, but also of white matter connectivity that links gray matter regions into distributed neural networks that subserve cognition and emotion.
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Równiak M, Bogus‐Nowakowska K, Kalinowski D, Kozłowska A. The evolutionary trajectories of the individual amygdala nuclei in the common shrew, guinea pig, rabbit, fox and pig: A consequence of embryological fate and mosaic-like evolution. J Anat 2022; 240:489-502. [PMID: 34648181 PMCID: PMC8819052 DOI: 10.1111/joa.13571] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 10/01/2021] [Accepted: 10/05/2021] [Indexed: 11/30/2022] Open
Abstract
The amygdala primarily evolved as a danger detector that regulates emotional behaviours and learning. However, it is also engaged in stress responses as well as olfactory/pheromonal and reproductive functions. All of these functions are processed by a set of nuclei which are derived from different telencephalic sources (pallial and subpallial) and have a unique cellular structure and specific connections. It is unclear how these individual anatomical and functional units evolved to fit the amygdala to the specific needs of various mammals. Thus, this study provides quantitative data regarding volumes, neuron density and neuron numbers in the main amygdala nuclei of the common shrew, guinea pig, rabbit, fox and pig - species from across the mammalian phylogeny which differ in brain complexity and ecology. The results show that the volume of the amygdala and its individual nuclei scale with negative allometry relative to brain mass (an allometric coefficient below one). However, in relation to the whole amygdala volume, volumes and volumetric percentages of the lateral (LA) and basomedial (BM) nuclei scale with positive allometry, for the medial (ME) and lateral olfactory tract (NLOT) nuclei these parameters scale with negative allometry while the values of these parameters for the basolateral (BL), central (CE) and cortical (CO) nuclei scale with isometry. Moreover, density of neurons scales with strong negative allometry relative to both brain mass and amygdala volume with values of allometric coefficient below zero across studied species. This value for BL is significantly lower than that for the whole amygdala, for ME it is significantly higher while values for NLOT, CE, CO, LA and BM are quite similar to the value for whole amygdala. Finally, neuron numbers in the whole amygdala and its individual nuclei scale with negative allometry in relation to brain mass. However, in relation to the number of neurons in the whole amygdala, neuron numbers and percentages of neurons for LA and BM scale with positive allometry, for BL and NLOT they scale with negative allometry while the values of these parameters for CE, CO and ME scale with isometry. In conclusion, all of these results indicate that each of the nuclei studied displays a different and unique pattern of evolution in relation to brain mass or the whole amygdala volume. These patterns do not match with the various classical concepts of amygdala parcellation; however, in some way, they reflect diversity revealed by the expression of homeobox genes in various embryological studies.
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Affiliation(s)
- Maciej Równiak
- Department of Animal Anatomy and PhysiologyFaculty of Biology and BiotechnologyUniversity of Warmia and Mazury in OlsztynOlsztynPoland
| | - Krystyna Bogus‐Nowakowska
- Department of Animal Anatomy and PhysiologyFaculty of Biology and BiotechnologyUniversity of Warmia and Mazury in OlsztynOlsztynPoland
| | - Daniel Kalinowski
- Department of Animal Anatomy and PhysiologyFaculty of Biology and BiotechnologyUniversity of Warmia and Mazury in OlsztynOlsztynPoland
| | - Anna Kozłowska
- Department of Human Physiology and PathophysiologySchool of MedicineUniversity of Warmia and Mazury in OlsztynOlsztynPoland
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33
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Rasia-Filho AA. Unraveling Brain Microcircuits, Dendritic Spines, and Synaptic Processing Using Multiple Complementary Approaches. Front Physiol 2022; 13:831568. [PMID: 35295578 PMCID: PMC8918670 DOI: 10.3389/fphys.2022.831568] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 01/26/2022] [Indexed: 12/21/2022] Open
Affiliation(s)
- Alberto A. Rasia-Filho
- Department of Basic Sciences/Physiology, Graduate Program in Biosciences, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, Brazil
- Graduate Program in Neuroscience, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
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34
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Stingo-Hirmas D, Cunha F, Cardoso RF, Carra LG, Rönnegård L, Wright D, Henriksen R. Proportional Cerebellum Size Predicts Fear Habituation in Chickens. Front Physiol 2022; 13:826178. [PMID: 35250629 PMCID: PMC8891606 DOI: 10.3389/fphys.2022.826178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 01/17/2022] [Indexed: 11/13/2022] Open
Abstract
The cerebellum has a highly conserved neural structure across species but varies widely in size. The wide variation in cerebellar size (both absolute and in proportion to the rest of the brain) among species and populations suggests that functional specialization is linked to its size. There is increasing recognition that the cerebellum contributes to cognitive processing and emotional control in addition to its role in motor coordination. However, to what extent cerebellum size reflects variation in these behavioral processes within species remains largely unknown. By using a unique intercross chicken population based on parental lines with high divergence in cerebellum size, we compared the behavior of individuals repeatedly exposed to the same fear test (emergence test) early in life and after sexual maturity (eight trials per age group) with proportional cerebellum size and cerebellum neural density. While proportional cerebellum size did not predict the initial fear response of the individuals (trial 1), it did increasingly predict adult individuals response as the trials progressed. Our results suggest that proportional cerebellum size does not necessarily predict an individual’s fear response, but rather the habituation process to a fearful stimulus. Cerebellum neuronal density did not predict fear behavior in the individuals which suggests that these effects do not result from changes in neuronal density but due to other variables linked to proportional cerebellum size which might underlie fear habituation.
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Affiliation(s)
| | - Felipe Cunha
- IFM-Biology, Linköping University, Linköping, Sweden
| | | | | | - Lars Rönnegård
- School of Technology and Business Studies, Dalarna University, Falun, Sweden
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | | | - Rie Henriksen
- IFM-Biology, Linköping University, Linköping, Sweden
- *Correspondence: Rie Henriksen,
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35
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Muratore IB, Fandozzi EM, Traniello JFA. Behavioral performance and division of labor influence brain mosaicism in the leafcutter ant Atta cephalotes. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 2022; 208:325-344. [PMID: 35112161 DOI: 10.1007/s00359-021-01539-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 12/27/2021] [Accepted: 12/28/2021] [Indexed: 11/29/2022]
Abstract
Brain evolution is hypothesized to be driven by behavioral selection on neuroarchitecture. We developed a novel metric of relative neuroanatomical investments involved in performing tasks varying in sensorimotor and processing demands across polymorphic task-specialized workers of the leafcutter ant Atta cephalotes and quantified brain size and structure to examine their correlation with our computational approximations. Investment in multisensory and motor integration for task performance was estimated to be greatest for media workers, whose highly diverse repertoire includes leaf-quality discrimination and leaf-harvesting tasks that likely involve demanding sensory and motor processes. Confocal imaging revealed that absolute brain volume increased with worker size and functionally specialized compartmental scaling differed among workers. The mushroom bodies, centers of sensory integration and learning and memory, and the antennal lobes, olfactory input sites, were larger in medias than in minims (gardeners) and significantly larger than in majors ("soldiers"), both of which had lower scores for involvement of olfactory processing in the performance of their characteristic tasks. Minims had a proportionally larger central complex compared to other workers. These results support the hypothesis that variation in task performance influences selection for mosaic brain structure, the independent evolution of proportions of the brain composed of different neuropils.
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Affiliation(s)
- I B Muratore
- Department of Biology, Boston University, Boston, MA, 02215, USA.
| | - E M Fandozzi
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - J F A Traniello
- Department of Biology, Boston University, Boston, MA, 02215, USA.,Graduate Program in Neuroscience, Boston University, Boston, MA, 02215, USA
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36
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Cerebral cortical processing time is elongated in human brain evolution. Sci Rep 2022; 12:1103. [PMID: 35058509 PMCID: PMC8776799 DOI: 10.1038/s41598-022-05053-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 01/04/2022] [Indexed: 11/09/2022] Open
Abstract
An increase in number of neurons is presumed to underlie the enhancement of cognitive abilities in brain evolution. The evolution of human cognition is then expected to have accompanied a prolongation of net neural-processing time due to the accumulation of processing time of individual neurons over an expanded number of neurons. Here, we confirmed this prediction and quantified the amount of prolongation in vivo, using noninvasive measurements of brain responses to sounds in unanesthetized human and nonhuman primates. Latencies of the N1 component of auditory-evoked potentials recorded from the scalp were approximately 40, 50, 60, and 100 ms for the common marmoset, rhesus monkey, chimpanzee, and human, respectively. Importantly, the prominent increase in human N1 latency could not be explained by the physical lengthening of the auditory pathway, and therefore reflected an extended dwell time for auditory cortical processing. A longer time window for auditory cortical processing is advantageous for analyzing time-varying acoustic stimuli, such as those important for speech perception. A novel hypothesis concerning human brain evolution then emerges: the increase in cortical neuronal number widened the timescale of sensory cortical processing, the benefits of which outweighed the disadvantage of slow cognition and reaction.
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37
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Mikhalkin AA, Merkulyeva NS. Peculiarities of Age-Related Dynamics of Neurons in the Cat Lateral Geniculate Nucleus as Revealed in Frontal versus Sagittal Slices. J EVOL BIOCHEM PHYS+ 2021. [DOI: 10.1134/s0022093021050021] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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38
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Makarova AA, Polilov AA, Chklovskii DB. Small brains for big science. Curr Opin Neurobiol 2021; 71:77-83. [PMID: 34656052 DOI: 10.1016/j.conb.2021.09.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 08/30/2021] [Accepted: 09/06/2021] [Indexed: 01/03/2023]
Abstract
As the study of the human brain is complicated by its sheer scale, complexity, and impracticality of invasive experiments, neuroscience research has long relied on model organisms. The brains of macaque, mouse, zebrafish, fruit fly, nematode, and others have yielded many secrets that advanced our understanding of the human brain. Here, we propose that adding miniature insects to this collection would reduce the costs and accelerate brain research. The smallest insects occupy a special place among miniature animals: despite their body sizes, comparable to unicellular organisms, they retain complex brains that include thousands of neurons. Their brains possess the advantages of those in insects, such as neuronal identifiability and the connectome stereotypy, yet are smaller and hence easier to map and understand. Finally, the brains of miniature insects offer insights into the evolution of brain design.
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Affiliation(s)
| | - Alexey A Polilov
- Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia
| | - Dmitri B Chklovskii
- CCN, Flatiron Institute and Neuroscience Institute, NYUMC, New York, United States.
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39
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Cunha F, Gutiérrez-Ibáñez C, Racicot K, Wylie DR, Iwaniuk AN. A quantitative analysis of cerebellar anatomy in birds. Brain Struct Funct 2021; 226:2561-2583. [PMID: 34357439 DOI: 10.1007/s00429-021-02352-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 07/26/2021] [Indexed: 12/19/2022]
Abstract
The cerebellum is largely conserved in its circuitry, but varies greatly in size and shape across species. The extent to which differences in cerebellar morphology is driven by changes in neuron numbers, neuron sizes or both, remains largely unknown. To determine how species variation in cerebellum size and shape is reflective of neuron sizes and numbers requires the development of a suitable comparative data set and one that can effectively separate different neuronal populations. Here, we generated the largest comparative dataset to date on neuron numbers, sizes, and volumes of cortical layers and surface area of the cerebellum across 54 bird species. Across different cerebellar sizes, the cortical layers maintained relatively constant proportions to one another and variation in cerebellum size was largely due to neuron numbers rather than neuron sizes. However, the rate at which neuron numbers increased with cerebellum size varied across Purkinje cells, granule cells, and cerebellar nuclei neurons. We also examined the relationship among neuron numbers, cerebellar surface area and cerebellar folding. Our estimate of cerebellar folding, the midsagittal foliation index, was a poor predictor of surface area and number of Purkinje cells, but surface area was the best predictor of Purkinje cell numbers. Overall, this represents the first comprehensive, quantitative analysis of cerebellar anatomy in a comparative context of any vertebrate. The extent to which these relationships occur in other vertebrates requires a similar approach and would determine whether the same scaling principles apply throughout the evolution of the cerebellum.
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Affiliation(s)
- Felipe Cunha
- Department of Neuroscience, University of Lethbridge, 4401 University Dr. W, Science & Academic Building, SA8150, Lethbridge, AB, T1K 6T5, Canada.
| | | | - Kelsey Racicot
- Department of Neuroscience, University of Lethbridge, 4401 University Dr. W, Science & Academic Building, SA8150, Lethbridge, AB, T1K 6T5, Canada
| | - Douglas R Wylie
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada
| | - Andrew N Iwaniuk
- Department of Neuroscience, University of Lethbridge, 4401 University Dr. W, Science & Academic Building, SA8150, Lethbridge, AB, T1K 6T5, Canada
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40
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Swiegers J, Bhagwandin A, Maseko BC, Sherwood CC, Hård T, Bertelsen MF, Spocter MA, Molnár Z, Manger PR. The distribution, number, and certain neurochemical identities of infracortical white matter neurons in the brains of a southern lesser galago, a black-capped squirrel monkey, and a crested macaque. J Comp Neurol 2021; 529:3676-3708. [PMID: 34259349 DOI: 10.1002/cne.25216] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 07/01/2021] [Accepted: 07/10/2021] [Indexed: 12/20/2022]
Abstract
In the current study, we examined the number, distribution, and aspects of the neurochemical identities of infracortical white matter neurons, also termed white matter interstitial cells (WMICs), in the brains of a southern lesser galago (Galago moholi), a black-capped squirrel monkey (Saimiri boliviensis boliviensis), and a crested macaque (Macaca nigra). Staining for neuronal nuclear marker (NeuN) revealed WMICs throughout the infracortical white matter, these cells being most dense close to inner cortical border, decreasing in density with depth in the white matter. Stereological analysis of NeuN-immunopositive cells revealed estimates of approximately 1.1, 10.8, and 37.7 million WMICs within the infracortical white matter of the galago, squirrel monkey, and crested macaque, respectively. The total numbers of WMICs form a distinct negative allometric relationship with brain mass and white matter volume when examined in a larger sample of primates where similar measures have been obtained. In all three primates studied, the highest densities of WMICs were in the white matter of the frontal lobe, with the occipital lobe having the lowest. Immunostaining revealed significant subpopulations of WMICs containing neuronal nitric oxide synthase (nNOS) and calretinin, with very few WMICs containing parvalbumin, and none containing calbindin. The nNOS and calretinin immunopositive WMICs represent approximately 21% of the total WMIC population; however, variances in the proportions of these neurochemical phenotypes were noted. Our results indicate that both the squirrel monkey and crested macaque might be informative animal models for the study of WMICs in neurodegenerative and psychiatric disorders in humans.
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Affiliation(s)
- Jordan Swiegers
- School of Anatomical Sciences, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Adhil Bhagwandin
- School of Anatomical Sciences, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Busisiwe C Maseko
- School of Anatomical Sciences, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Chet C Sherwood
- Department of Anthropology, Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, District of Columbia, USA
| | | | - Mads F Bertelsen
- Centre for Zoo and Wild Animal Health, Copenhagen Zoo, Frederiksberg, Denmark
| | - Muhammad A Spocter
- School of Anatomical Sciences, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.,Department of Anatomy, Des Moines University, Des Moines, Iowa, USA
| | - Zoltán Molnár
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK
| | - Paul R Manger
- School of Anatomical Sciences, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
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41
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Abstract
Energy constraints are a fundamental limitation of the brain, which is physically embedded in a restricted space. The collective dynamics of neurons through connections enable the brain to achieve rich functionality, but building connections and maintaining activity come at a high cost. The effects of reducing these costs can be found in the characteristic structures of the brain network. Nevertheless, the mechanism by which energy constraints affect the organization and formation of the neuronal network in the brain is unclear. Here, it is shown that a simple model based on cost minimization can reproduce structures characteristic of the brain network. With reference to the behavior of neurons in real brains, the cost function was introduced in an activity-dependent form correlating the activity cost and the wiring cost as a simple ratio. Cost reduction of this ratio resulted in strengthening connections, especially at highly activated nodes, and induced the formation of large clusters. Regarding these network features, statistical similarity was confirmed by comparison to connectome datasets from various real brains. The findings indicate that these networks share an efficient structure maintained with low costs, both for activity and for wiring. These results imply the crucial role of energy constraints in regulating the network activity and structure of the brain.
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42
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Avin S, Currie A, Montgomery SH. An agent-based model clarifies the importance of functional and developmental integration in shaping brain evolution. BMC Biol 2021; 19:97. [PMID: 33971877 PMCID: PMC8111752 DOI: 10.1186/s12915-021-01024-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Accepted: 04/13/2021] [Indexed: 01/01/2023] Open
Abstract
Background Vertebrate brain structure is characterised not only by relative consistency in scaling between components, but also by many examples of divergence from these general trends.. Alternative hypotheses explain these patterns by emphasising either ‘external’ processes, such as coordinated or divergent selection, or ‘internal’ processes, like developmental coupling among brain regions. Although these hypotheses are not mutually exclusive, there is little agreement over their relative importance across time or how that importance may vary across evolutionary contexts. Results We introduce an agent-based model to simulate brain evolution in a ‘bare-bones’ system and examine dependencies between variables shaping brain evolution. We show that ‘concerted’ patterns of brain evolution do not, in themselves, provide evidence for developmental coupling, despite these terms often being treated as synonymous in the literature. Instead, concerted evolution can reflect either functional or developmental integration. Our model further allows us to clarify conditions under which such developmental coupling, or uncoupling, is potentially adaptive, revealing support for the maintenance of both mechanisms in neural evolution. Critically, we illustrate how the probability of deviation from concerted evolution depends on the cost/benefit ratio of neural tissue, which increases when overall brain size is itself under constraint. Conclusions We conclude that both developmentally coupled and uncoupled brain architectures can provide adaptive mechanisms, depending on the distribution of selection across brain structures, life history and costs of neural tissue. However, when constraints also act on overall brain size, heterogeneity in selection across brain structures will favour region specific, or mosaic, evolution. Regardless, the respective advantages of developmentally coupled and uncoupled brain architectures mean that both may persist in fluctuating environments. This implies that developmental coupling is unlikely to be a persistent constraint, but could evolve as an adaptive outcome to selection to maintain functional integration.
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Affiliation(s)
- Shahar Avin
- Centre for the Study of Existential Risk, University of Cambridge, Cambridge, UK
| | - Adrian Currie
- Department of Sociology, Philosophy and Anthropology, University of Exeter, Exeter, UK
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Godfrey RK, Swartzlander M, Gronenberg W. Allometric analysis of brain cell number in Hymenoptera suggests ant brains diverge from general trends. Proc Biol Sci 2021; 288:20210199. [PMID: 33757353 PMCID: PMC8059961 DOI: 10.1098/rspb.2021.0199] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2021] [Accepted: 02/26/2021] [Indexed: 12/12/2022] Open
Abstract
Many comparative neurobiological studies seek to connect sensory or behavioural attributes across taxa with differences in their brain composition. Recent studies in vertebrates suggest cell number and density may be better correlated with behavioural ability than brain mass or volume, but few estimates of such figures exist for insects. Here, we use the isotropic fractionator (IF) method to estimate total brain cell numbers for 32 species of Hymenoptera spanning seven subfamilies. We find estimates from using this method are comparable to traditional, whole-brain cell counts of two species and to published estimates from established stereological methods. We present allometric scaling relationships between body and brain mass, brain mass and nuclei number, and body mass and cell density and find that ants stand out from bees and wasps as having particularly small brains by measures of mass and cell number. We find that Hymenoptera follow the general trend of smaller animals having proportionally larger brains. Smaller Hymenoptera also feature higher brain cell densities than the larger ones, as is the case in most vertebrates, but in contrast with primates, in which neuron density remains rather constant across changes in brain mass. Overall, our findings establish the IF as a useful method for comparative studies of brain size evolution in insects.
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Affiliation(s)
- R. Keating Godfrey
- Department of Neuroscience, University of Arizona, Tucson, AZ 85721, USA
- Department of Molecular and Cellular Biology, University of Arizona, Tucson, AZ 85721, USA
| | | | - Wulfila Gronenberg
- Department of Neuroscience, University of Arizona, Tucson, AZ 85721, USA
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44
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Rasia-Filho AA, Guerra KTK, Vásquez CE, Dall’Oglio A, Reberger R, Jung CR, Calcagnotto ME. The Subcortical-Allocortical- Neocortical continuum for the Emergence and Morphological Heterogeneity of Pyramidal Neurons in the Human Brain. Front Synaptic Neurosci 2021; 13:616607. [PMID: 33776739 PMCID: PMC7991104 DOI: 10.3389/fnsyn.2021.616607] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Accepted: 02/01/2021] [Indexed: 11/13/2022] Open
Abstract
Human cortical and subcortical areas integrate emotion, memory, and cognition when interpreting various environmental stimuli for the elaboration of complex, evolved social behaviors. Pyramidal neurons occur in developed phylogenetic areas advancing along with the allocortex to represent 70-85% of the neocortical gray matter. Here, we illustrate and discuss morphological features of heterogeneous spiny pyramidal neurons emerging from specific amygdaloid nuclei, in CA3 and CA1 hippocampal regions, and in neocortical layers II/III and V of the anterolateral temporal lobe in humans. Three-dimensional images of Golgi-impregnated neurons were obtained using an algorithm for the visualization of the cell body, dendritic length, branching pattern, and pleomorphic dendritic spines, which are specialized plastic postsynaptic units for most excitatory inputs. We demonstrate the emergence and development of human pyramidal neurons in the cortical and basomedial (but not the medial, MeA) nuclei of the amygdala with cells showing a triangular cell body shape, basal branched dendrites, and a short apical shaft with proximal ramifications as "pyramidal-like" neurons. Basomedial neurons also have a long and distally ramified apical dendrite not oriented to the pial surface. These neurons are at the beginning of the allocortex and the limbic lobe. "Pyramidal-like" to "classic" pyramidal neurons with laminar organization advance from the CA3 to the CA1 hippocampal regions. These cells have basal and apical dendrites with specific receptive synaptic domains and several spines. Neocortical pyramidal neurons in layers II/III and V display heterogeneous dendritic branching patterns adapted to the space available and the afferent inputs of each brain area. Dendritic spines vary in their distribution, density, shapes, and sizes (classified as stubby/wide, thin, mushroom-like, ramified, transitional forms, "atypical" or complex forms, such as thorny excrescences in the MeA and CA3 hippocampal region). Spines were found isolated or intermingled, with evident particularities (e.g., an extraordinary density in long, deep CA1 pyramidal neurons), and some showing a spinule. We describe spiny pyramidal neurons considerably improving the connectional and processing complexity of the brain circuits. On the other hand, these cells have some vulnerabilities, as found in neurodegenerative Alzheimer's disease and in temporal lobe epilepsy.
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Affiliation(s)
- Alberto A. Rasia-Filho
- Department of Basic Sciences/Physiology and Graduate Program in Biosciences, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, Brazil
- Graduate Program in Neuroscience, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Kétlyn T. Knak Guerra
- Graduate Program in Neuroscience, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Carlos Escobar Vásquez
- Graduate Program in Neuroscience, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Aline Dall’Oglio
- Department of Basic Sciences/Physiology and Graduate Program in Biosciences, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, Brazil
| | - Roman Reberger
- Medical Engineering Program, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Cláudio R. Jung
- Institute of Informatics, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Maria Elisa Calcagnotto
- Graduate Program in Neuroscience, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Neurophysiology and Neurochemistry of Neuronal Excitability and Synaptic Plasticity Laboratory, Department of Biochemistry and Biochemistry Graduate Program, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
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Mbiydzenyuy NE, Pieme CA, Brown RE, Nguemeni C. Neuroscience education and research in Cameroon: Current status and future direction. IBRO Neurosci Rep 2021; 10:216-224. [PMID: 34179870 PMCID: PMC8211920 DOI: 10.1016/j.ibneur.2021.02.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 12/22/2020] [Accepted: 02/10/2021] [Indexed: 11/26/2022] Open
Abstract
Neurological disorders comprise 20% of hospital admissions in Cameroon. The burden of neurological disorders is increasing, especially in children and the elderly. However, there are very few neurologists, psychiatrists, gerontologists and neuropsychologists trained in the treatment of neurological disorders in Cameroon and there are very few facilities for training in basic and clinical neuroscience. Although non-governmental organizations such as the International Brain Research Organization (IBRO), International Society of Neurochemistry (ISN), and Teaching and Research in Natural Sciences for Development (TReND) in Africa have stepped in to provide short training courses and workshops in neuroscience, these are neither sufficient to train African neuroscientists nor to build the capacity to train neuroscience researchers and clinicians. There has also been little support from universities and the government for such training. While some participants of these schools have managed to form collaborations with foreign researchers and have been invited to study abroad, this does not facilitate the training of neuroscientists in Cameroon. Moreover, the research infrastructure for training in neuroscience remains limited. This is reflected in the low research output from Cameroonian universities in the field. In this review, we describe the burden of neurological disorders in Cameroon and outline the outstanding efforts of local scientists to develop the discipline of neuroscience, which is still an emerging field in Cameroon. We identify key actionable steps towards the improvement of the scientific capacity in neuroscience in Cameroon: (1) develop targeted neuroscience training programs in all major universities in Cameroon; (2) implement a thriving scientific environment supported by international collaborations; (3) focus on the leadership and the mentorship of both local and senior neuroscientists; (4) develop public awareness and information of policy makers to increase governmental funding for neuroscience research. Improving scientific capacity to tackle the neurological diseases burden in Cameroon is urgent. Neuroscience schools and advocated researchers shape the future of neuroscience in Cameroon. Public-private partnerships are required for sustainable country impact of neuroscience schools.
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Affiliation(s)
- Ngala Elvis Mbiydzenyuy
- Department of Basic Medical Science, School of Medicine, Copperbelt University, Ndola, Zambia
| | | | - Richard E Brown
- Department of Psychology and Neuroscience, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Carine Nguemeni
- Department of Neurology, University Hospital of Würzburg, Germany
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Ho CLA, Zimmermann R, Flórez Weidinger JD, Prsa M, Schottdorf M, Merlin S, Okamoto T, Ikezoe K, Pifferi F, Aujard F, Angelucci A, Wolf F, Huber D. Orientation Preference Maps in Microcebus murinus Reveal Size-Invariant Design Principles in Primate Visual Cortex. Curr Biol 2020; 31:733-741.e7. [PMID: 33275889 PMCID: PMC9026768 DOI: 10.1016/j.cub.2020.11.027] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2020] [Revised: 10/08/2020] [Accepted: 11/11/2020] [Indexed: 01/05/2023]
Abstract
Orientation preference maps (OPMs) are a prominent feature of primary visual cortex (V1) organization in many primates and carnivores. In rodents, neurons are not organized in OPMs but are instead interspersed in a “salt and pepper” fashion, although clusters of orientation-selective neurons have been reported. Does this fundamental difference reflect the existence of a lower size limit for orientation columns (OCs) below which they cannot be scaled down with decreasing V1 size? To address this question, we examined V1 of one of the smallest living primates, the 60-g prosimian mouse lemur (Microcebus murinus). Using chronic intrinsic signal imaging, we found that mouse lemur V1 contains robust OCs, which are arranged in a pinwheel-like fashion. OC size in mouse lemurs was found to be only marginally smaller compared to the macaque, suggesting that these circuit elements are nearly incompressible. The spatial arrangement of pinwheels is well described by a common mathematical design of primate V1 circuit organization. In order to accommodate OPMs, we found that the mouse lemur V1 covers one-fifth of the cortical surface, which is one of the largest V1-to-cortex ratios found in primates. These results indicate that the primate-type visual cortical circuit organization is constrained by a size limitation and raises the possibility that its emergence might have evolved by disruptive innovation rather than gradual change. Orientation preference maps are a hallmark of V1 organization in all primates studied thus far, yet they are absent in rodents. It is uncertain whether these structures scale with body or brain size. Using intrinsic signal imaging, Ho et al. reveal the presence of such maps in the V1 of the world’s smallest primate, the mouse lemur (Microcebus murinus).
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Affiliation(s)
- Chun Lum Andy Ho
- University of Geneva, Department of Basic Neurosciences, Rue Michel Servet 1, Geneva 1211, Switzerland
| | - Robert Zimmermann
- University of Geneva, Department of Basic Neurosciences, Rue Michel Servet 1, Geneva 1211, Switzerland
| | | | - Mario Prsa
- University of Geneva, Department of Basic Neurosciences, Rue Michel Servet 1, Geneva 1211, Switzerland
| | - Manuel Schottdorf
- Max Planck Institute for Dynamics and Self-Organization, Am Faßberg 17, Göttingen 37077, Germany
| | - Sam Merlin
- Moran Eye Center, University of Utah, Department of Ophthalmology and Visual Science, 65 Mario Capecchi Drive, Salt Lake City, UT 84132, USA
| | - Tsuyoshi Okamoto
- Kyushu University, Faculty of Arts and Science, 744 Motooka Nishi-ku, Fukuoka 819-0395, Japan
| | - Koji Ikezoe
- Center for Information and Neural Networks, Osaka University and National Institute of Information and Communications Technology, Graduate School of Frontier Biosciences, 1-3 Yamadaoka Suita, Osaka 565-0871, Japan
| | - Fabien Pifferi
- UMR CNRS/MNHN 7179, Mécanismes Adaptatifs et Evolution, 1 Avenue du Petit Chateau, Brunoy 91800, France
| | - Fabienne Aujard
- UMR CNRS/MNHN 7179, Mécanismes Adaptatifs et Evolution, 1 Avenue du Petit Chateau, Brunoy 91800, France
| | - Alessandra Angelucci
- Moran Eye Center, University of Utah, Department of Ophthalmology and Visual Science, 65 Mario Capecchi Drive, Salt Lake City, UT 84132, USA
| | - Fred Wolf
- Max Planck Institute for Dynamics and Self-Organization, Am Faßberg 17, Göttingen 37077, Germany; Campus Institute for Dynamics of Biological Networks, Hermann-Rein-Straße 3, Göttingen 37075, Germany; Bernstein Center for Computational Neuroscience, Hermann-Rein-Straße 3, Göttingen 37075, Germany; Max Planck Institute of Experimental Medicine, Hermann-Rein-Straße 3, Göttingen 37075, Germany; Institute for Dynamics of Complex Systems, Georg-August University, Friedrich-Hund-Platz 1, Göttingen 37073, Germany
| | - Daniel Huber
- University of Geneva, Department of Basic Neurosciences, Rue Michel Servet 1, Geneva 1211, Switzerland.
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Numerical Analysis of the Cerebral Cortex in Diprotodontids (Marsupialia; Australidelphia) and Comparison with Eutherian Brains. ZOOLOGY 2020; 143:125845. [DOI: 10.1016/j.zool.2020.125845] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 09/09/2020] [Accepted: 09/11/2020] [Indexed: 11/22/2022]
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Neves K, Guercio GD, Anjos-Travassos Y, Costa S, Perozzo A, Montezuma K, Herculano-Houzel S, Panizzutti R. The relationship between the number of neurons and behavioral performance in Swiss mice. Neurosci Lett 2020; 735:135202. [PMID: 32599318 DOI: 10.1016/j.neulet.2020.135202] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Accepted: 06/21/2020] [Indexed: 10/24/2022]
Abstract
Neuronal number varies by several orders of magnitude across species, and has been proposed to predict cognitive capability across species. Remarkably, numbers of neurons vary across individual mice by a factor of 2 or more. We directly addressed the question of whether there is a relationship between performance in behavioral tests and the number of neurons in functionally relevant structures in the mouse brain. Naïve Swiss mice went through a battery of behavioral tasks designed to measure cognitive, motor and olfactory skills. We estimated the number of neurons in different brain regions (cerebral cortex, hippocampus, olfactory bulb, cerebellum and remaining areas) and crossed the two datasets to test the a priori hypothesis of correlation between cognitive abilities and numbers of neurons. Surprisingly, performance in the behavioral tasks did not correlate strongly with number of neurons in any of the brain regions studied. Our results show that whereas neuronal number is a predictor of cognitive skills across species, it is not a good predictor of cognitive, sensory or motor ability across individuals within a species, which suggests that other factors are more relevant for explaining cognitive differences between individuals of the same species.
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Affiliation(s)
- Kleber Neves
- Instituto de Bioquímica Médica Leopoldo de Meis, Universidade Federal do Rio de Janeiro, Brazil; Instituto de Ciências Biomédicas, Universidade Federal do Rio de Janeiro, Brazil.
| | - Gerson Duarte Guercio
- Instituto de Ciências Biomédicas, Universidade Federal do Rio de Janeiro, Brazil; Department of Psychiatry, University of Minnesota, 2312 S 6th St., Minneapolis, MN, United States.
| | - Yuri Anjos-Travassos
- Instituto de Ciências Biomédicas, Universidade Federal do Rio de Janeiro, Brazil
| | - Stella Costa
- Instituto de Ciências Biomédicas, Universidade Federal do Rio de Janeiro, Brazil
| | - Ananda Perozzo
- Instituto de Ciências Biomédicas, Universidade Federal do Rio de Janeiro, Brazil
| | - Karine Montezuma
- Instituto de Ciências Biomédicas, Universidade Federal do Rio de Janeiro, Brazil
| | - Suzana Herculano-Houzel
- Department of Psychology, Department of Biological Sciences, Vanderbilt Brain Institute, Vanderbilt University, United States
| | - Rogério Panizzutti
- Instituto de Ciências Biomédicas, Universidade Federal do Rio de Janeiro, Brazil; Instituto de Psiquiatria, Universidade Federal do Rio de Janeiro, Brazil
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Storks L, Powell BJ, Leal M. Peeking Inside the Lizard Brain: Neuron Numbers in Anolis and Its Implications for Cognitive Performance and Vertebrate Brain Evolution. Integr Comp Biol 2020; 63:icaa129. [PMID: 33175153 DOI: 10.1093/icb/icaa129] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Studies of vertebrate brain evolution have mainly focused on measures of brain size, particularly relative mass and its allometric scaling across lineages, commonly with the goal of identifying the substrates that underly differences in cognition. However, recent studies on birds and mammals have demonstrated that brain size is an imperfect proxy for neuronal parameters that underly function, such as the number of neurons that make up a given brain region. Here we present estimates of neuron numbers and density in two species of lizard, Anolis cristatellus and A. evermanni, representing the first such data from squamate species, and explore its implications for differences in cognitive performance and vertebrate brain evolution. The isotropic fractionator protocol outlined in this article is optimized for the unique challenges that arise when using this technique with lineages having nucleated erythrocytes and relatively small brains. The number and density of neurons and other cells we find in Anolis for the telencephalon, cerebellum, and the rest of the brain (ROB) follow similar patterns as published data from other vertebrate species. Anolis cristatellus and A. evermanni exhibited differences in their performance in a motor task frequently used to evaluate behavioral flexibility, which was not mirrored by differences in the number, density, or proportion of neurons in either the cerebellum, telencephalon, or ROB. However, the brain of A. evermanni had a significantly higher number of nonneurons and a higher nonneuron to neuron ratio across the whole brain, which could contribute to the observed differences in problem solving between A. cristatellus and A. evermanni. Although limited to two species, our findings suggest that neuron number and density in lizard brains scale similarly to endothermic vertebrates in contrast to the differences observed in brain to body mass relationships. Data from a wider range of species are necessary before we can fully understand vertebrate brain evolution at the neuronal level.
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Affiliation(s)
- Levi Storks
- Division of Biological Sciences, University of Missouri, Columbia, MO, USA
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Bauer GB, Cook PF, Harley HE. The Relevance of Ecological Transitions to Intelligence in Marine Mammals. Front Psychol 2020; 11:2053. [PMID: 33013519 PMCID: PMC7505747 DOI: 10.3389/fpsyg.2020.02053] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Accepted: 07/24/2020] [Indexed: 12/26/2022] Open
Abstract
Macphail's comparative approach to intelligence focused on associative processes, an orientation inconsistent with more multifaceted lay and scientific understandings of the term. His ultimate emphasis on associative processes indicated few differences in intelligence among vertebrates. We explore options more attuned to common definitions by considering intelligence in terms of richness of representations of the world, the interconnectivity of those representations, the ability to flexibly change those connections, and knowledge. We focus on marine mammals, represented by the amphibious pinnipeds and the aquatic cetaceans and sirenians, as animals that transitioned from a terrestrial existence to an aquatic one, experiencing major changes in ecological pressures. They adapted with morphological transformations related to streamlining the body, physiological changes in respiration and thermoregulation, and sensory/perceptual changes, including echolocation capabilities and diminished olfaction in many cetaceans, both in-air and underwater visual focus, and enhanced senses of touch in pinnipeds and sirenians. Having a terrestrial foundation on which aquatic capacities were overlaid likely affected their cognitive abilities, especially as a new reliance on sound and touch, and the need to surface to breath changed their interactions with the world. Vocal and behavioral observational learning capabilities in the wild and in laboratory experiments suggest versatility in group coordination. Empirical reports on aspects of intelligent behavior like problem-solving, spatial learning, and concept learning by various species of cetaceans and pinnipeds suggest rich cognitive abilities. The high energy demands of the brain suggest that brain-intelligence relationships might be fruitful areas for study when specific hypotheses are considered, e.g., brain mapping indicates hypertrophy of specific sensory areas in marine mammals. Modern neuroimaging techniques provide ways to study neural connectivity, and the patterns of connections between sensory, motor, and other cortical regions provide a biological framework for exploring how animals represent and flexibly use information in navigating and learning about their environment. At this stage of marine mammal research, it would still be prudent to follow Macphail's caution that it is premature to make strong comparative statements without more empirical evidence, but an approach that includes learning more about how animals flexibly link information across multiple representations could be a productive way of comparing species by allowing them to use their specific strengths within comparative tasks.
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Affiliation(s)
- Gordon B. Bauer
- Division of Social Sciences, New College of Florida, Sarasota, FL, United States
- Mote Marine Laboratory, Sarasota, FL, United States
| | - Peter F. Cook
- Division of Social Sciences, New College of Florida, Sarasota, FL, United States
- Mote Marine Laboratory, Sarasota, FL, United States
| | - Heidi E. Harley
- Division of Social Sciences, New College of Florida, Sarasota, FL, United States
- Mote Marine Laboratory, Sarasota, FL, United States
- The Seas, Epcot, Walt Disney World Resorts, Lake Buena Vista, FL, United States
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