1
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Spani F, Carducci F, Piervincenzi C, Ben-Soussan TD, Mallio CA, Quattrocchi CC. Assessing brain neuroplasticity: Surface morphometric analysis of cortical changes induced by Quadrato motor training. J Anat 2024. [PMID: 38924527 DOI: 10.1111/joa.14104] [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: 03/21/2024] [Revised: 05/27/2024] [Accepted: 06/12/2024] [Indexed: 06/28/2024] Open
Abstract
Morphological markers for brain plasticity are still lacking and their findings are challenged by the extreme variability of cortical brain surface. Trying to overcome the "correspondence problem," we applied a landmark-free method (the generalized procrustes surface analysis (GPSA)) for investigating the shape variation of cortical surface in a group of 40 healthy volunteers (i.e., the practice group) subjected to daily motor training known as Quadrato motor training (QMT). QMT is a sensorimotor walking meditation that aims at balancing body, cognition, and emotion. More specifically, QMT requires coordination and attention and consists of moving in one of three possible directions on corners of a 50 × 50 cm2. Brain magnetic resonance images (MRIs) of practice group (acquired at baseline, as well as after 6 and 12 weeks of QMT), were 3D reconstructed and here compared with brain MRIs of six more volunteers never practicing the QMT (naïve group). Cortical regions mostly affected by morphological variations were visualized on a 3D average color-scaled brain surface indicating from higher (red) to lower (blue) levels of variation. Cortical regions interested in most of the shape variations were as follows: (1) the supplementary motor cortex; (2) the inferior frontal gyrus (pars opercolaris) and the anterior insula; (3) the visual cortex; (4) the inferior parietal lobule (supramarginal gyrus and angular gyrus). Our results show that surface morphometric analysis (i.e., GPSA) can be applied to assess brain neuroplasticity processes, such as those stimulated by QMT.
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Affiliation(s)
- F Spani
- Department of Science and Technology for Sustainable Development and One Health, Università Campus Bio-Medico di Roma, Rome, Italy
| | - F Carducci
- Neuroimaging Laboratory, Department of Physiology and Pharmacology, Sapienza University of Rome (IT), Rome, Italy
| | - C Piervincenzi
- Department of Human Neurosciences, Sapienza University, Rome, Italy
| | - T D Ben-Soussan
- Research Institute for Neuroscience, Education and Didactics (RINED), Patrizio Paoletti Foundation, Assisi, Italy
| | - C A Mallio
- Department of Medicine and Surgery, Research Unit of Diagnostic Imaging, Università Campus Bio-Medico di Roma, Rome, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Operative Research Unit of Diagnostic Imaging and Interventional Radiology, Rome, Italy
| | - C C Quattrocchi
- Centre for Medical Sciences-CISMed, University of Trento, Trento, Italy
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2
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Magielse N, Toro R, Steigauf V, Abbaspour M, Eickhoff SB, Heuer K, Valk SL. Phylogenetic comparative analysis of the cerebello-cerebral system in 34 species highlights primate-general expansion of cerebellar crura I-II. Commun Biol 2023; 6:1188. [PMID: 37993596 PMCID: PMC10665558 DOI: 10.1038/s42003-023-05553-z] [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: 03/16/2023] [Accepted: 11/07/2023] [Indexed: 11/24/2023] Open
Abstract
The reciprocal connections between the cerebellum and the cerebrum have been suggested to simultaneously play a role in brain size increase and to support a broad array of brain functions in primates. The cerebello-cerebral system has undergone marked functionally relevant reorganization. In particular, the lateral cerebellar lobules crura I-II (the ansiform) have been suggested to be expanded in hominoids. Here, we manually segmented 63 cerebella (34 primate species; 9 infraorders) and 30 ansiforms (13 species; 8 infraorders) to understand how their volumes have evolved over the primate lineage. Together, our analyses support proportional cerebellar-cerebral scaling, whereas ansiforms have expanded faster than the cerebellum and cerebrum. We did not find different scaling between strepsirrhines and haplorhines, nor between apes and non-apes. In sum, our study shows primate-general structural reorganization of the ansiform, relative to the cerebello-cerebral system, which is relevant for specialized brain functions in an evolutionary context.
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Grants
- RT and KH are supported by the French Agence Nationale de la Recherche, projects NeuroWebLab (ANR-19-DATA-0025) and DMOBE (ANR-21-CE45-0016). KH received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No101033485 (Individual Fellowship). Last, this work was funded in part by Helmholtz Association’s Initiative and Networking Fund under the Helmholtz International Lab grant agreement InterLabs-0015, and the Canada First Research Excellence Fund (CFREF Competition 2, 2015–2016), awarded to the Healthy Brains, Healthy Lives initiative at McGill University, through the Helmholtz International BigBrain Analytics and Learning Laboratory (HIBALL), including NM, SBE, and SLV.
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Affiliation(s)
- Neville Magielse
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Center Jülich, Wilhelm-Johnen-Straße, 52428, Jülich, Germany.
- Otto Hahn Cognitive Neurogenetics Group, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1A, 04103, Leipzig, Germany.
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Moorenstraße 5, 40225, Düsseldorf, Germany.
| | - Roberto Toro
- Institut Pasteur, Unité de Neuroanatomie Appliquée et Théorique, Université Paris Cité, 25 rue du Dr. Roux, 75724, Paris, France
| | - Vanessa Steigauf
- Department of Biology, Northern Michigan University, 1401 Presque Isle Ave, MI, 49855, Marquette, USA
| | - Mahta Abbaspour
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Luisenstraße 56, Haus 1, 10117, Berlin, Germany
- Department of Neurology, Charité - Universitätsmedizin Berlin, Bonhoefferweg 3, 10117, Berlin, Germany
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Center Jülich, Wilhelm-Johnen-Straße, 52428, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Moorenstraße 5, 40225, Düsseldorf, Germany
| | - Katja Heuer
- Institut Pasteur, Unité de Neuroanatomie Appliquée et Théorique, Université Paris Cité, 25 rue du Dr. Roux, 75724, Paris, France
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1A, 04103, Leipzig, Germany
| | - Sofie L Valk
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Center Jülich, Wilhelm-Johnen-Straße, 52428, Jülich, Germany.
- Otto Hahn Cognitive Neurogenetics Group, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1A, 04103, Leipzig, Germany.
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Moorenstraße 5, 40225, Düsseldorf, Germany.
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3
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Dunbar RIM, Shultz S. Four errors and a fallacy: pitfalls for the unwary in comparative brain analyses. Biol Rev Camb Philos Soc 2023; 98:1278-1309. [PMID: 37001905 DOI: 10.1111/brv.12953] [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: 09/09/2022] [Revised: 03/17/2023] [Accepted: 03/17/2023] [Indexed: 04/03/2023]
Abstract
Comparative analyses are the backbone of evolutionary analysis. However, their record in producing a consensus has not always been good. This is especially true of attempts to understand the factors responsible for the evolution of large brains, which have been embroiled in an increasingly polarised debate over the past three decades. We argue that most of these disputes arise from a number of conceptual errors and associated logical fallacies that are the result of a failure to adopt a biological systems-based approach to hypothesis-testing. We identify four principal classes of error: a failure to heed Tinbergen's Four Questions when testing biological hypotheses, misapplying Dobzhansky's Dictum when testing hypotheses of evolutionary adaptation, poorly chosen behavioural proxies for underlying hypotheses, and the use of inappropriate statistical methods. In the interests of progress, we urge a more careful and considered approach to comparative analyses, and the adoption of a broader, rather than a narrower, taxonomic perspective.
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Affiliation(s)
- Robin I M Dunbar
- Department of Experimental Psychology, Anna Watts Building, University of Oxford, Oxford, OX2 6GG, UK
| | - Susanne Shultz
- Department of Earth and Environmental Sciences, Michael Smith Building, University of Manchester, Manchester, M13 9PT, UK
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4
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DeCasien AR, Barton RA, Higham JP. Understanding the human brain: insights from comparative biology. Trends Cogn Sci 2022; 26:432-445. [DOI: 10.1016/j.tics.2022.02.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 01/27/2022] [Accepted: 02/08/2022] [Indexed: 02/08/2023]
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5
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de Chevalier G, Bouret S, Bardo A, Simmen B, Garcia C, Prat S. Cost-Benefit Trade-Offs of Aquatic Resource Exploitation in the Context of Hominin Evolution. Front Ecol Evol 2022. [DOI: 10.3389/fevo.2022.812804] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
While the exploitation of aquatic fauna and flora has been documented in several primate species to date, the evolutionary contexts and mechanisms behind the emergence of this behavior in both human and non-human primates remain largely overlooked. Yet, this issue is particularly important for our understanding of human evolution, as hominins represent not only the primate group with the highest degree of adaptedness to aquatic environments, but also the only group in which true coastal and maritime adaptations have evolved. As such, in the present study we review the available literature on primate foraging strategies related to the exploitation of aquatic resources and their putative associated cognitive operations. We propose that aquatic resource consumption in extant primates can be interpreted as a highly site-specific behavioral expression of a generic adaptive foraging decision-making process, emerging in sites at which the local cost-benefit trade-offs contextually favor aquatic over terrestrial foods. Within this framework, we discuss the potential impacts that the unique intensification of this behavior in hominins may have had on the evolution of the human brain and spatial ecology.
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7
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Dunbar RIM, Shultz S. Social complexity and the fractal structure of group size in primate social evolution. Biol Rev Camb Philos Soc 2021; 96:1889-1906. [PMID: 33945202 DOI: 10.1111/brv.12730] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Revised: 04/17/2021] [Indexed: 12/25/2022]
Abstract
Compared to most other mammals and birds, anthropoid primates have unusually complex societies characterised by bonded social groups. Among primates, this effect is encapsulated in the social brain hypothesis: the robust correlation between various indices of social complexity (social group size, grooming clique size, tactical behaviour, coalition formation) and brain size. Hitherto, this has always been interpreted as a simple, unitary relationship. Using data for five different indices of brain volume from four independent brain databases, we show that the distribution of group size plotted against brain size is best described as a set of four distinct, very narrowly defined grades which are unrelated to phylogeny. The allocation of genera to these grades is highly consistent across the different data sets and brain indices. We show that these grades correspond to the progressive evolution of bonded social groups. In addition, we show, for those species that live in multilevel social systems, that the typical sizes of the different grouping levels in each case coincide with different grades. This suggests that the grades correspond to demographic attractors that are especially stable. Using five different cognitive indices, we show that the grades correlate with increasing social cognitive skills, suggesting that the cognitive demands of managing group cohesion increase progressively across grades. We argue that the grades themselves represent glass ceilings on animals' capacity to maintain social and spatial coherence during foraging and that, in order to evolve more highly bonded groups, species have to be able to invest in costly forms of cognition.
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Affiliation(s)
- Robin I M Dunbar
- Department of Experimental Psychology, Radcliffe Observatory Quarter, University of Oxford, Oxford, OX2 1GG, UK
| | - Susanne Shultz
- Department of Earth and Environmental Sciences, Michael Smith Building, University of Manchester, Manchester, M13 9PT, UK
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8
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Lindenfors P, Wartel A, Lind J. 'Dunbar's number' deconstructed. Biol Lett 2021; 17:20210158. [PMID: 33947220 PMCID: PMC8103230 DOI: 10.1098/rsbl.2021.0158] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Accepted: 04/14/2021] [Indexed: 12/14/2022] Open
Abstract
A widespread and popular belief posits that humans possess a cognitive capacity that is limited to keeping track of and maintaining stable relationships with approximately 150 people. This influential number, 'Dunbar's number', originates from an extrapolation of a regression line describing the relationship between relative neocortex size and group size in primates. Here, we test if there is statistical support for this idea. Our analyses on complementary datasets using different methods yield wildly different numbers. Bayesian and generalized least-squares phylogenetic methods generate approximations of average group sizes between 69-109 and 16-42, respectively. However, enormous 95% confidence intervals (4-520 and 2-336, respectively) imply that specifying any one number is futile. A cognitive limit on human group size cannot be derived in this manner.
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Affiliation(s)
- Patrik Lindenfors
- Institute for Futures Studies, Box 591, 101 31 Stockholm, Sweden
- Centre for Cultural Evolution, Stockholm University, Sweden
| | - Andreas Wartel
- Centre for Cultural Evolution, Stockholm University, Sweden
| | - Johan Lind
- Centre for Cultural Evolution, Stockholm University, Sweden
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9
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DeCasien AR, Higham JP. Relative Cerebellum Size Is Not Sexually Dimorphic across Primates. BRAIN, BEHAVIOR AND EVOLUTION 2020; 95:93-101. [PMID: 32791505 DOI: 10.1159/000509070] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Accepted: 06/02/2020] [Indexed: 11/19/2022]
Abstract
BACKGROUND/AIMS Substantive sex differences in behavior and cognition are found in humans and other primates. However, potential sex differences in primate neuroanatomy remain largely unexplored. Here, we investigate sex differences in the relative size of the cerebellum, a region that has played a major role in primate brain evolution and that has been associated with cognitive abilities that may be subject to sexual selection in primates. METHODS We compiled individual volumetric and sex data from published data sources and used MCMC generalized linear mixed models to test for sex effects in relative cerebellar volume while controlling for phylogenetic relationships between species. Given that the cerebellum is a functionally heterogeneous structure involved in multiple complex cognitive processes that may be under selection in males or females within certain species, and that sexual selection pressures vary so greatly across primate species, we predicted there would be no sex difference in the relative size of the cerebellum across primates. RESULTS Our results support our prediction, suggesting there is no consistent sex difference in relative cerebellum size. CONCLUSION This work suggests that the potential for sex differences in relative cerebellum size has been subject to either developmental constraint or lack of consistent selection pressures, and highlights the need for more individual-level primate neuroanatomical data to facilitate intra- and inter-specific study of brain sexual dimorphism.
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Affiliation(s)
- Alex R DeCasien
- Department of Anthropology, New York University, New York, New York, USA, .,New York Consortium in Evolutionary Primatology, New York, New York, USA,
| | - James P Higham
- Department of Anthropology, New York University, New York, New York, USA.,New York Consortium in Evolutionary Primatology, New York, New York, USA
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10
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Sherwood CC, Miller SB, Karl M, Stimpson CD, Phillips KA, Jacobs B, Hof PR, Raghanti MA, Smaers JB. Invariant Synapse Density and Neuronal Connectivity Scaling in Primate Neocortical Evolution. Cereb Cortex 2020; 30:5604-5615. [PMID: 32488266 DOI: 10.1093/cercor/bhaa149] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Revised: 03/31/2020] [Accepted: 05/07/2020] [Indexed: 12/20/2022] Open
Abstract
Synapses are involved in the communication of information from one neuron to another. However, a systematic analysis of synapse density in the neocortex from a diversity of species is lacking, limiting what can be understood about the evolution of this fundamental aspect of brain structure. To address this, we quantified synapse density in supragranular layers II-III and infragranular layers V-VI from primary visual cortex and inferior temporal cortex in a sample of 25 species of primates, including humans. We found that synapse densities were relatively constant across these levels of the cortical visual processing hierarchy and did not significantly differ with brain mass, varying by only 1.9-fold across species. We also found that neuron densities decreased in relation to brain enlargement. Consequently, these data show that the number of synapses per neuron significantly rises as a function of brain expansion in these neocortical areas of primates. Humans displayed the highest number of synapses per neuron, but these values were generally within expectations based on brain size. The metabolic and biophysical constraints that regulate uniformity of synapse density, therefore, likely underlie a key principle of neuronal connectivity scaling in primate neocortical evolution.
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Affiliation(s)
- Chet C Sherwood
- Department of Anthropology, Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, DC 20052, USA
| | - Sarah B Miller
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH 03755, USA
| | - Molly Karl
- Department of Anthropology, Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, DC 20052, USA
| | - Cheryl D Stimpson
- Department of Anthropology, Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, DC 20052, USA
| | | | - Bob Jacobs
- Department of Psychology, Laboratory of Quantitative Neuromorphology, Colorado College, Colorado Springs, CO 80946, USA
| | - Patrick R Hof
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Mary Ann Raghanti
- Department of Anthropology, School of Biomedical Sciences, Brain Health Research Institute, Kent State University, Kent, OH 44242, USA
| | - Jeroen B Smaers
- Department of Anthropology, Stony Brook University, Stony Brook, NY 11794, USA.,Division of Anthropology, American Museum of Natural History, New York, NY 10024, USA
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11
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Fernandes HB, Peñaherrera-Aguirre M, Woodley of Menie MA, Figueredo AJ. Macroevolutionary patterns and selection modes for general intelligence (G) and for commonly used neuroanatomical volume measures in primates. INTELLIGENCE 2020. [DOI: 10.1016/j.intell.2020.101456] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
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12
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Seymour RS, Bosiocic V, Snelling EP, Chikezie PC, Hu Q, Nelson TJ, Zipfel B, Miller CV. Cerebral blood flow rates in recent great apes are greater than in Australopithecus species that had equal or larger brains. Proc Biol Sci 2019; 286:20192208. [PMID: 31718497 DOI: 10.1098/rspb.2019.2208] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Brain metabolic rate (MR) is linked mainly to the cost of synaptic activity, so may be a better correlate of cognitive ability than brain size alone. Among primates, the sizes of arterial foramina in recent and fossil skulls can be used to evaluate brain blood flow rate, which is proportional to brain MR. We use this approach to calculate flow rate in the internal carotid arteries (Q˙ICA), which supply most of the primate cerebrum. Q˙ICA is up to two times higher in recent gorillas, chimpanzees and orangutans compared with 3-million-year-old australopithecine human relatives, which had equal or larger brains. The scaling relationships between Q˙ICA and brain volume (Vbr) show exponents of 1.03 across 44 species of living haplorhine primates and 1.41 across 12 species of fossil hominins. Thus, the evolutionary trajectory for brain perfusion is much steeper among ancestral hominins than would be predicted from living primates. Between 4.4-million-year-old Ardipithecus and Homo sapiens, Vbr increased 4.7-fold, but Q˙ICA increased 9.3-fold, indicating an approximate doubling of metabolic intensity of brain tissue. By contrast, Q˙ICA is proportional to Vbr among haplorhine primates, suggesting a constant volume-specific brain MR.
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Affiliation(s)
- Roger S Seymour
- School of Biological Sciences, Faculty of Sciences, University of Adelaide, Adelaide, South Australia 5005, Australia
| | - Vanya Bosiocic
- School of Biological Sciences, Faculty of Sciences, University of Adelaide, Adelaide, South Australia 5005, Australia
| | - Edward P Snelling
- Department of Anatomy and Physiology, Faculty of Veterinary Science, University of Pretoria, Onderstepoort 0110, South Africa.,Brain Function Research Group, School of Physiology, University of the Witwatersrand, Johannesburg 2193, South Africa
| | - Prince C Chikezie
- Brain Function Research Group, School of Physiology, University of the Witwatersrand, Johannesburg 2193, South Africa
| | - Qiaohui Hu
- School of Biological Sciences, Faculty of Sciences, University of Adelaide, Adelaide, South Australia 5005, Australia
| | - Thomas J Nelson
- School of Biological Sciences, Faculty of Sciences, University of Adelaide, Adelaide, South Australia 5005, Australia
| | - Bernhard Zipfel
- Evolutionary Studies Institute, University of the Witwatersrand, Johannesburg 2193, South Africa
| | - Case V Miller
- Vertebrate Palaeontology Laboratory, Department of Earth Sciences, University of Hong Kong, Pok Fu Lam, Hong Kong
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13
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Serio C, Castiglione S, Tesone G, Piccolo M, Melchionna M, Mondanaro A, Di Febbraro M, Raia P. Macroevolution of Toothed Whales Exceptional Relative Brain Size. Evol Biol 2019. [DOI: 10.1007/s11692-019-09485-7] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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14
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Powell LE, Barton RA, Street SE. Maternal investment, life histories and the evolution of brain structure in primates. Proc Biol Sci 2019; 286:20191608. [PMID: 31530145 PMCID: PMC6784728 DOI: 10.1098/rspb.2019.1608] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Accepted: 08/15/2019] [Indexed: 12/16/2022] Open
Abstract
Life history is a robust correlate of relative brain size: larger-brained mammals and birds have slower life histories and longer lifespans than smaller-brained species. The cognitive buffer hypothesis (CBH) proposes an adaptive explanation for this relationship: large brains may permit greater behavioural flexibility and thereby buffer the animal from unpredictable environmental challenges, allowing for reduced mortality and increased lifespan. By contrast, the developmental costs hypothesis (DCH) suggests that life-history correlates of brain size reflect the extension of maturational processes needed to accommodate the evolution of large brains, predicting correlations with pre-adult life-history phases. Here, we test novel predictions of the hypotheses in primates applied to the neocortex and cerebellum, two major brain structures with distinct developmental trajectories. While neocortical growth is allocated primarily to pre-natal development, the cerebellum exhibits relatively substantial post-natal growth. Consistent with the DCH, neocortical expansion is related primarily to extended gestation while cerebellar expansion to extended post-natal development, particularly the juvenile period. Contrary to the CBH, adult lifespan explains relatively little variance in the whole brain or neocortex volume once pre-adult life-history phases are accounted for. Only the cerebellum shows a relationship with lifespan after accounting for developmental periods. Our results substantiate and elaborate on the role of maternal investment and offspring development in brain evolution, suggest that brain components can evolve partly independently through modifications of distinct developmental phases, and imply that environmental input during post-natal maturation may be particularly crucial for the development of cerebellar function. They also suggest that relatively extended post-natal maturation times provide a developmental mechanism for the marked expansion of the cerebellum in the apes.
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Affiliation(s)
- Lauren E. Powell
- Evolutionary Anthropology Research Group, Department of Anthropology, Durham University, South Road, Durham DH1 3LE, UK
| | | | - Sally E. Street
- Evolutionary Anthropology Research Group, Department of Anthropology, Durham University, South Road, Durham DH1 3LE, UK
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15
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DeCasien AR, Higham JP. Primate mosaic brain evolution reflects selection on sensory and cognitive specialization. Nat Ecol Evol 2019; 3:1483-1493. [PMID: 31548648 DOI: 10.1038/s41559-019-0969-0] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2018] [Accepted: 07/26/2019] [Indexed: 02/06/2023]
Abstract
The mammalian brain is composed of numerous functionally distinct structures that vary in size within and between clades, reflecting selection for sensory and cognitive specialization. Primates represent a particularly interesting case in which to examine mosaic brain evolution since they exhibit marked behavioural variation, spanning most social structures, diets and activity periods observed across mammals. Although studies have consistently demonstrated a trade-off between visual and olfactory specialization in primates, studies of some regions (for example, the neocortex) have produced conflicting results. Here, we analyse the socioecological factors influencing the relative size of 33 brain regions, using updated statistical techniques and data from more species and individuals than previous studies. Our results confirm that group-living species and those with high-quality diets have expanded olfactory or visual systems, depending on whether they are nocturnal or diurnal. Conversely, regions associated with spatial memory are expanded in solitary species and those with low-quality diets, suggesting a trade-off between visual processing and spatial memory. Contrary to previous work, we show that diet quality predicts relative neocortex size at least as well as, if not better than, social complexity. Overall, our results demonstrate that primate brain structure is largely driven by selection on sensory and cognitive specializations that develop in response to divergent socioecological niches.
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Affiliation(s)
- Alex R DeCasien
- Department of Anthropology, New York University, New York, NY, USA. .,New York Consortium in Evolutionary Primatology, New York, NY, USA.
| | - James P Higham
- Department of Anthropology, New York University, New York, NY, USA.,New York Consortium in Evolutionary Primatology, New York, NY, USA
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16
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Wartel A, Lindenfors P, Lind J. Whatever you want: Inconsistent results are the rule, not the exception, in the study of primate brain evolution. PLoS One 2019; 14:e0218655. [PMID: 31329603 PMCID: PMC6645455 DOI: 10.1371/journal.pone.0218655] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2018] [Accepted: 06/06/2019] [Indexed: 01/14/2023] Open
Abstract
Primate brains differ in size and architecture. Hypotheses to explain this variation are numerous and many tests have been carried out. However, after body size has been accounted for there is little left to explain. The proposed explanatory variables for the residual variation are many and covary, both with each other and with body size. Further, the data sets used in analyses have been small, especially in light of the many proposed predictors. Here we report the complete list of models that results from exhaustively combining six commonly used predictors of brain and neocortex size. This provides an overview of how the output from standard statistical analyses changes when the inclusion of different predictors is altered. By using both the most commonly tested brain data set and the inclusion of new data we show that the choice of included variables fundamentally changes the conclusions as to what drives primate brain evolution. Our analyses thus reveal why studies have had troubles replicating earlier results and instead have come to such different conclusions. Although our results are somewhat disheartening, they highlight the importance of scientific rigor when trying to answer difficult questions. It is our position that there is currently no empirical justification to highlight any particular hypotheses, of those adaptive hypotheses we have examined here, as the main determinant of primate brain evolution.
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Affiliation(s)
- Andreas Wartel
- Centre for Cultural Evolution and Department of Zoology Stockholm University, Stockholm, Sweden
| | - Patrik Lindenfors
- Centre for Cultural Evolution and Department of Zoology Stockholm University, Stockholm, Sweden
- Institute for Future Studies, Stockholm, Sweden
| | - Johan Lind
- Centre for Cultural Evolution and Department of Zoology Stockholm University, Stockholm, Sweden
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Milham MP, Ai L, Koo B, Xu T, Amiez C, Balezeau F, Baxter MG, Blezer ELA, Brochier T, Chen A, Croxson PL, Damatac CG, Dehaene S, Everling S, Fair DA, Fleysher L, Freiwald W, Froudist-Walsh S, Griffiths TD, Guedj C, Hadj-Bouziane F, Ben Hamed S, Harel N, Hiba B, Jarraya B, Jung B, Kastner S, Klink PC, Kwok SC, Laland KN, Leopold DA, Lindenfors P, Mars RB, Menon RS, Messinger A, Meunier M, Mok K, Morrison JH, Nacef J, Nagy J, Rios MO, Petkov CI, Pinsk M, Poirier C, Procyk E, Rajimehr R, Reader SM, Roelfsema PR, Rudko DA, Rushworth MFS, Russ BE, Sallet J, Schmid MC, Schwiedrzik CM, Seidlitz J, Sein J, Shmuel A, Sullivan EL, Ungerleider L, Thiele A, Todorov OS, Tsao D, Wang Z, Wilson CRE, Yacoub E, Ye FQ, Zarco W, Zhou YD, Margulies DS, Schroeder CE. An Open Resource for Non-human Primate Imaging. Neuron 2018; 100:61-74.e2. [PMID: 30269990 PMCID: PMC6231397 DOI: 10.1016/j.neuron.2018.08.039] [Citation(s) in RCA: 139] [Impact Index Per Article: 23.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2018] [Revised: 03/02/2018] [Accepted: 08/30/2018] [Indexed: 01/11/2023]
Abstract
Non-human primate neuroimaging is a rapidly growing area of research that promises to transform and scale translational and cross-species comparative neuroscience. Unfortunately, the technological and methodological advances of the past two decades have outpaced the accrual of data, which is particularly challenging given the relatively few centers that have the necessary facilities and capabilities. The PRIMatE Data Exchange (PRIME-DE) addresses this challenge by aggregating independently acquired non-human primate magnetic resonance imaging (MRI) datasets and openly sharing them via the International Neuroimaging Data-sharing Initiative (INDI). Here, we present the rationale, design, and procedures for the PRIME-DE consortium, as well as the initial release, consisting of 25 independent data collections aggregated across 22 sites (total = 217 non-human primates). We also outline the unique pitfalls and challenges that should be considered in the analysis of non-human primate MRI datasets, including providing automated quality assessment of the contributed datasets.
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Affiliation(s)
- Michael P Milham
- Center for the Developing Brain, Child Mind Institute, New York, NY 10022, USA; Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA.
| | - Lei Ai
- Center for the Developing Brain, Child Mind Institute, New York, NY 10022, USA
| | - Bonhwang Koo
- Center for the Developing Brain, Child Mind Institute, New York, NY 10022, USA
| | - Ting Xu
- Center for the Developing Brain, Child Mind Institute, New York, NY 10022, USA
| | - Céline Amiez
- University of Lyon, Université Claude Bernard Lyon 1, INSERM, Stem Cell and Brain Research Institute U1208, Lyon, France
| | - Fabien Balezeau
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Mark G Baxter
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Erwin L A Blezer
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Thomas Brochier
- Institut de Neurosciences de la Timone, CNRS & Aix-Marseille Université, UMR 7289, Marseille, France
| | - Aihua Chen
- Key Laboratory of Brain Functional Genomics (Ministry of Education & Science and Technology Commission of Shanghai Municipality), School of Life Sciences, East China Normal University, Shanghai 200062, China
| | - Paula L Croxson
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Christienne G Damatac
- Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen, 6525 EN Nijmegen, Netherlands
| | - Stanislas Dehaene
- NeuroSpin, CEA, INSERM U992, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
| | - Stefan Everling
- Centre for Functional and Metabolic Mapping, The University of Western Ontario, London, ON N6A 3K7, Canada
| | - Damian A Fair
- Department of Behavior Neuroscience, Department of Psychiatry, Advanced Imaging Research Center, Oregon Health and Science University, Portland, OR, USA
| | - Lazar Fleysher
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Winrich Freiwald
- Laboratory of Neural Systems, The Rockefeller University, New York, NY, USA
| | | | - Timothy D Griffiths
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Carole Guedj
- INSERM, U1028, CNRS UMR5292, Lyon Neuroscience Research Center, Lyon, France
| | | | - Suliann Ben Hamed
- Institut des Sciences Cognitives - Marc Jeannerod, UMR5229, CNRS-Université de Lyon, Lyon, France
| | - Noam Harel
- Center for Magnetic Resonance Research, University of Minnesota Medical School, Minneapolis, MN 55455, USA
| | - Bassem Hiba
- Institut des Sciences Cognitives - Marc Jeannerod, UMR5229, CNRS-Université de Lyon, Lyon, France
| | - Bechir Jarraya
- NeuroSpin, CEA, INSERM U992, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
| | - Benjamin Jung
- Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Sabine Kastner
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08540, USA
| | - P Christiaan Klink
- Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, 1105 BA Amsterdam, the Netherlands; Department of Psychiatry, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, the Netherlands
| | - Sze Chai Kwok
- Shanghai Key Laboratory of Brain Functional Genomics, School of Psychology and Cognitive Science, Key Laboratory of Brain Functional Genomics (Ministry of Education), East China Normal University, Shanghai 200062, China; Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai 200062, China; NYU-ECNU Institute of Brain and Cognitive Science at NYU Shanghai, Shanghai 200062, China
| | - Kevin N Laland
- Centre for Social Learning and Cognitive Evolution, School of Biology, University of St. Andrews, St. Andrews, UK
| | - David A Leopold
- Section on Cognitive Neurophysiology and Imaging, National Institute of Mental Health, Bethesda, MD 20892, USA; Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Eye Institute, Bethesda, MD 20892, USA
| | - Patrik Lindenfors
- Institute for Future Studies, Stockholm, Sweden; Centre for Cultural Evolution & Department of Zoology, Stockholm University, Stockholm, Sweden
| | - Rogier B Mars
- Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen, 6525 EN Nijmegen, Netherlands; Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford OX3 9DU, UK
| | - Ravi S Menon
- Centre for Functional and Metabolic Mapping, The University of Western Ontario, London, ON N6A 3K7, Canada
| | - Adam Messinger
- Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Martine Meunier
- INSERM, U1028, CNRS UMR5292, Lyon Neuroscience Research Center, Lyon, France
| | - Kelvin Mok
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Departments of Neurology, Neurosurgery, and Biomedical Engineering, McGill University, Montreal, QC H3A 0G4, Canada
| | - John H Morrison
- California National Primate Research Center, Davis, CA 95616, USA; Department of Neurology, School of Medicine, University of California, Davis, CA 95616, USA
| | - Jennifer Nacef
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Jamie Nagy
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Michael Ortiz Rios
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Christopher I Petkov
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Mark Pinsk
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08540, USA
| | - Colline Poirier
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Emmanuel Procyk
- University of Lyon, Université Claude Bernard Lyon 1, INSERM, Stem Cell and Brain Research Institute U1208, Lyon, France
| | - Reza Rajimehr
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Simon M Reader
- Department of Biology and Helmholtz Institute, Utrecht University, 35 84 CH Utrecht, The Netherlands; Department of Biology, McGill University, Montreal, QC H3A 1BA, Canada
| | - Pieter R Roelfsema
- Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, 1105 BA Amsterdam, the Netherlands; Department of Psychiatry, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, the Netherlands; Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit, 1081 HV Amsterdam, the Netherlands
| | - David A Rudko
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Departments of Neurology, Neurosurgery, and Biomedical Engineering, McGill University, Montreal, QC H3A 0G4, Canada
| | - Matthew F S Rushworth
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford OX3 9DU, UK; Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford OX1 3AQ, UK
| | - Brian E Russ
- Section on Cognitive Neurophysiology and Imaging, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Jerome Sallet
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford OX1 3AQ, UK
| | | | | | - Jakob Seidlitz
- Developmental Neurogenomics Unit, National Institute of Mental Health, Bethesda, MD 20892, USA; Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, UK
| | - Julien Sein
- Institut de Neurosciences de la Timone, CNRS & Aix-Marseille Université, UMR 7289, Marseille, France
| | - Amir Shmuel
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Departments of Neurology, Neurosurgery, and Biomedical Engineering, McGill University, Montreal, QC H3A 0G4, Canada
| | - Elinor L Sullivan
- Divisions of Neuroscience and Cardiometabolic Health, Oregon National Primate Research Center, Beaverton, OR, USA; Department of Human Physiology, University of Oregon, Eugene, OR, USA
| | - Leslie Ungerleider
- Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Alexander Thiele
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Orlin S Todorov
- Department of Biology and Helmholtz Institute, Utrecht University, 35 84 CH Utrecht, The Netherlands
| | - Doris Tsao
- Department of Computation and Neural Systems, California Institute of Technology, Pasadena, CA 91125, USA
| | - Zheng Wang
- Institute of Neuroscience, Key Laboratory of Primate Neurobiology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Charles R E Wilson
- University of Lyon, Université Claude Bernard Lyon 1, INSERM, Stem Cell and Brain Research Institute U1208, Lyon, France
| | - Essa Yacoub
- Center for Magnetic Resonance Research, University of Minnesota Medical School, Minneapolis, MN 55455, USA
| | - Frank Q Ye
- Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Eye Institute, Bethesda, MD 20892, USA
| | - Wilbert Zarco
- Laboratory of Neural Systems, The Rockefeller University, New York, NY, USA
| | - Yong-di Zhou
- Krieger Mind/Brain Institute, Department of Neurosurgery, Johns Hopkins University, Baltimore, MD 21287, USA
| | - Daniel S Margulies
- Max Planck Research Group for Neuroanatomy and Connectivity, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany; Centre national de la recherche scientifique, CNRS UMR 7225, Institut du Cerveau et de la Moelle épinière, 75013 Paris, France
| | - Charles E Schroeder
- Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA; Department of Neurological Surgery, Columbia University College of Physicians and Surgeons, New York, NY 10032, USA; Department of Psychiatry, Columbia University College of Physicians and Surgeons, New York, NY 10032, USA
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